{ "built": "2026-10-27", "master": "danielrosehill/Read-Aloud-Voice-Sentences", "blends": { "cs": { "line": "Jachnun (and the first Shakshuka runs)", "rule": "code-switching rows, Daniel's own English (about 2/3 of the English share), LibriSpeech-PC replay, plus the task tags ['currency']" }, "all": { "line": "Sabich, Shakshuka v1.0+ and the Sabich variants", "rule": "every row of the master dataset at the run's revision, including every task tag present then, except ['name-cipher', 'paragraphs', 'weird-voices']; replay about 10%. From Sabich v2.1, priority-word takes (Hebrish/ASR-Error-List) appear 3 times." } }, "models": [ { "id": "danielrosehill/Parakeet-TDT-0.6B-v2-English-Hebrew-Codeswitching", "line": "Jachnun", "version": "PoC-1", "run": "pilot-en30", "released": "2026-10-15", "task": "speech-recognition", "base": null, "trained_on": [ "danielrosehill/Read-Aloud-Voice-Sentences" ], "blend": "cs", "dataset_revision": "b31aeabb5edc", "minutes": null, "rows": null, "evidence": "ASR-Training data/checkpoints.json (pilot-en30)", "confidence": "confirmed" }, { "id": "danielrosehill/Parakeet-TDT-0.6B-v2-English-Hebrew-Codeswitching", "line": "Jachnun", "version": "PoC-2", "run": "r2-en30", "released": "2026-10-15", "task": "speech-recognition", "base": null, "trained_on": [ "danielrosehill/Read-Aloud-Voice-Sentences" ], "blend": "cs", "dataset_revision": "3bdaa2a50d52", "minutes": null, "rows": null, "evidence": "ASR-Training data/checkpoints.json (r2-en30)", "confidence": "confirmed" }, { "id": "danielrosehill/Parakeet-TDT-0.6B-v2-English-Hebrew-Codeswitching", "line": "Jachnun", "version": "PoC-3", "run": "r3-en30", "released": "2026-10-18", "task": "speech-recognition", "base": null, "trained_on": [ "danielrosehill/Read-Aloud-Voice-Sentences" ], "blend": "cs", "dataset_revision": "b47310621f79", "minutes": null, "rows": null, "evidence": "ASR-Training data/checkpoints.json (r3-en30)", "confidence": "confirmed" }, { "id": "danielrosehill/Parakeet-TDT-0.6B-v2-English-Hebrew-Codeswitching", "line": "Jachnun", "version": "PoC-4", "run": "r4-en30", "released": "2026-10-18", "task": "speech-recognition", "base": null, "trained_on": [ "danielrosehill/Read-Aloud-Voice-Sentences" ], "blend": "cs", "dataset_revision": "4fcca820e0c2", "minutes": null, "rows": null, "evidence": "ASR-Training data/checkpoints.json (r4-en30)", "confidence": "confirmed" }, { "id": "danielrosehill/Parakeet-TDT-0.6B-v2-English-Hebrew-Codeswitching", "line": "Jachnun", "version": "PoC-5", "run": "r5-en30", "released": "2026-10-18", "task": "speech-recognition", "base": "nvidia/parakeet-tdt-0.6b-v2", "trained_on": [ "danielrosehill/Read-Aloud-Voice-Sentences" ], "blend": "cs", "dataset_revision": "fcf5aec16449", "minutes": null, "rows": null, "evidence": "ASR-Training data/checkpoints.json (r5-en30)", "confidence": "confirmed" }, { "id": "Hebrish/Nemotron-Speech-Streaming-EN-0.6B-English-Hebrew-Codeswitching", "line": "Shakshuka", "version": "PoC-1", "run": "r5-nemotron-en30", "released": "2026-10-18", "task": "speech-recognition", "base": "nvidia/nemotron-speech-streaming-en-0.6b", "trained_on": [ "danielrosehill/Read-Aloud-Voice-Sentences" ], "blend": "cs", "dataset_revision": "fcf5aec16449", "minutes": null, "rows": null, "evidence": "ASR-Training data/checkpoints.json (r5-nemotron-en30)", "confidence": "confirmed" }, { "id": "danielrosehill/Parakeet-TDT-0.6B-v2-English-Hebrew-Codeswitching", "line": "Jachnun", "version": "v1.0", "run": "r6-en30", "released": "2026-10-19", "task": "speech-recognition", "base": "nvidia/parakeet-tdt-0.6b-v2", "trained_on": [ "danielrosehill/Read-Aloud-Voice-Sentences" ], "blend": "cs", "dataset_revision": "550bfcaa0f84", "minutes": null, "rows": null, "evidence": "ASR-Training data/checkpoints.json (r6-en30)", "confidence": "confirmed" }, { "id": "Hebrish/Nemotron-Speech-Streaming-EN-0.6B-English-Hebrew-Codeswitching", "line": "Shakshuka", "version": "PoC-2", "run": "r6-nemotron-en30", "released": "2026-10-19", "task": "speech-recognition", "base": "nvidia/nemotron-speech-streaming-en-0.6b", "trained_on": [ "danielrosehill/Read-Aloud-Voice-Sentences" ], "blend": "cs", "dataset_revision": "550bfcaa0f84", "minutes": null, "rows": null, "evidence": "ASR-Training data/checkpoints.json (r6-nemotron-en30)", "confidence": "confirmed" }, { "id": "Hebrish/Sabich", "line": "Sabich", "version": "v1.0", "run": "r7-all", "released": "2026-10-20", "task": "speech-recognition", "base": "nvidia/parakeet-tdt-0.6b-v2", "trained_on": [ "danielrosehill/Read-Aloud-Voice-Sentences" ], "blend": "all", "dataset_revision": "f956dbb184c2", "minutes": 623.0, "rows": 5334, "evidence": "ASR-Training data/checkpoints.json (r7-all)", "confidence": "confirmed" }, { "id": "Hebrish/Shakshuka", "line": "Shakshuka", "version": "v1.0", "run": "r8-nemotron-all", "released": "2026-10-21", "task": "speech-recognition", "base": "nvidia/nemotron-speech-streaming-en-0.6b", "trained_on": [ "danielrosehill/Read-Aloud-Voice-Sentences" ], "blend": "all", "dataset_revision": "e918e381e831", "minutes": 658.4, "rows": 5634, "evidence": "ASR-Training data/checkpoints.json (r8-nemotron-all)", "confidence": "confirmed" }, { "id": "Hebrish/Sabich-Parakeet-110M", "line": "Sabich-Parakeet-110M", "version": "v1.0", "run": "r8-ctc110m-all", "released": "2026-10-21", "task": "speech-recognition", "base": "nvidia/parakeet-tdt_ctc-110m", "trained_on": [ "danielrosehill/Read-Aloud-Voice-Sentences" ], "blend": "all", "dataset_revision": "e918e381e831", "minutes": 658.4, "rows": 5634, "evidence": "ASR-Training data/checkpoints.json (r8-ctc110m-all)", "confidence": "confirmed" }, { "id": "Hebrish/Sabich-Qwen3-ASR-1.7B", "line": "Sabich-Qwen3-ASR-1.7B", "version": "PoC", "run": "q1-all", "released": null, "task": "speech-recognition", "base": "Qwen/Qwen3-ASR-1.7B", "trained_on": [ "danielrosehill/Read-Aloud-Voice-Sentences" ], "blend": "all", "dataset_revision": "e918e381e831", "minutes": 658.4, "rows": 5634, "evidence": "ASR-Training data/checkpoints.json (q1-all)", "confidence": "confirmed" }, { "id": "Hebrish/Sabich-Canary-Qwen-2.5B", "line": "Sabich-Canary-Qwen-2.5B", "version": "v1.0", "run": "cq1-all", "released": "2026-10-21", "task": "speech-recognition", "base": "nvidia/canary-qwen-2.5b", "trained_on": [ "danielrosehill/Read-Aloud-Voice-Sentences" ], "blend": "all", "dataset_revision": "cf84f7e45d78", "minutes": 669.3, "rows": 5752, "evidence": "ASR-Training data/checkpoints.json (cq1-all)", "confidence": "confirmed" }, { "id": "Hebrish/Sabich-asr4all-M", "line": "Sabich-asr4all-M", "version": "v1.0", "run": "a1-all", "released": "2026-10-21", "task": "speech-recognition", "base": "futo-org/asr4all-m", "trained_on": [ "danielrosehill/Read-Aloud-Voice-Sentences" ], "blend": "all", "dataset_revision": "cf84f7e45d78", "minutes": 669.3, "rows": 5752, "evidence": "ASR-Training data/checkpoints.json (a1-all)", "confidence": "confirmed" }, { "id": "Hebrish/Sabich-asr4all-S", "line": "Sabich-asr4all-S", "version": "v1.0", "run": "a1s-all", "released": "2026-10-21", "task": "speech-recognition", "base": "futo-org/asr4all-s", "trained_on": [ "danielrosehill/Read-Aloud-Voice-Sentences" ], "blend": "all", "dataset_revision": "cf84f7e45d78", "minutes": 669.3, "rows": 5752, "evidence": "ASR-Training data/checkpoints.json (a1s-all)", "confidence": "confirmed" }, { "id": "Hebrish/Sabich", "line": "Sabich", "version": "v2.0", "run": "r9-all", "released": "2026-10-22", "task": "speech-recognition", "base": "nvidia/parakeet-tdt-0.6b-v2", "trained_on": [ "danielrosehill/Read-Aloud-Voice-Sentences" ], "blend": "all", "dataset_revision": "110d144a0502", "minutes": 713.9, "rows": 6225, "evidence": "ASR-Training data/checkpoints.json (r9-all)", "confidence": "confirmed" }, { "id": "Hebrish/Shakshuka", "line": "Shakshuka", "version": "v2.0", "run": "r9-nemotron-all", "released": "2026-10-22", "task": "speech-recognition", "base": "nvidia/nemotron-speech-streaming-en-0.6b", "trained_on": [ "danielrosehill/Read-Aloud-Voice-Sentences" ], "blend": "all", "dataset_revision": "110d144a0502", "minutes": 713.9, "rows": 6225, "evidence": "ASR-Training data/checkpoints.json (r9-nemotron-all)", "confidence": "confirmed" }, { "id": "Hebrish/Sabich", "line": "Sabich", "version": "v2.1", "run": "r10-all", "released": "2026-10-25", "task": "speech-recognition", "base": "nvidia/parakeet-tdt-0.6b-v2", "trained_on": [ "danielrosehill/Read-Aloud-Voice-Sentences" ], "blend": "all", "dataset_revision": "2cec2ebc85e9", "minutes": 848.4, "rows": 7765, "evidence": "ASR-Training data/checkpoints.json (r10-all)", "confidence": "confirmed" }, { "id": "Hebrish/Meorav", "line": "Meorav", "version": "v2.1", "released": "2026-10-22", "task": "text-to-speech", "base": "Qwen3-TTS", "trained_on": [ "Hebrish/Hebrish-TTS-Voice-Recordings" ], "data_note": "train split, 1,103 takes (v2.0 and v2.1)", "evidence": "Hebrish/Meorav model card", "confidence": "confirmed" }, { "id": "Hebrish/Meorav", "line": "Meorav", "version": "v2.0", "released": "2026-10-22", "task": "text-to-speech", "base": "Qwen3-TTS", "trained_on": [ "Hebrish/Hebrish-TTS-Voice-Recordings" ], "data_note": "train split, 1,103 takes; replaced by v2.1 the same day", "evidence": "Hebrish/Meorav model card", "confidence": "confirmed" }, { "id": "Hebrish/TTS-V1", "line": "Meorav", "version": "PoC-1", "released": "2026-10-22", "task": "text-to-speech", "base": "Qwen3-TTS", "trained_on": [ "Hebrish/Hebrish-TTS-Voice-Recordings" ], "data_note": "657 read takes, 50 min after trimming (run first-test); the repo is no longer on the Hub (404 on 2026-10-27)", "evidence": "Meorav-TTS README, model table", "confidence": "confirmed" }, { "id": "danielrosehill/Whisper-Hebrish", "line": "Whisper-Hebrish", "version": "v2", "task": "speech-recognition", "base": "openai/whisper-large-v3-turbo", "trained_on": [ "danielrosehill/Read-Aloud-Voice-Sentences" ], "data_note": "1,929 training rows / 215 min, mostly phone takes, 29% monolingual English; term-disjoint test split", "evidence": "model card, 'What changed from v1'", "confidence": "confirmed" }, { "id": "Hebrish/Whisper-Hebrish-Small-ACFT", "line": "Whisper-Hebrish", "version": "small, ACFT", "task": "speech-recognition", "base": "openai/whisper-small", "trained_on": [ "danielrosehill/Read-Aloud-Voice-Sentences" ], "data_note": "same 1,929 training clips and mix as Whisper-Hebrish v2", "evidence": "model card, 'Training'", "confidence": "confirmed" }, { "id": "Hebrish/Hebrew-Latin-Token-Classifier", "line": "Token classifier", "version": "v1", "task": "token-classification", "trained_on": [ "Hebrish/hebrew-latin-code-switching" ], "data_note": "4,737 sentences; marks the romanized Hebrew words in English text (TTS chain)", "evidence": "model card", "confidence": "confirmed" } ], "datasets": [ { "id": "danielrosehill/Read-Aloud-Voice-Sentences", "title": "Read-Aloud Voice Sentences (master)", "kind": "audio-takes", "tag": null, "description": "Every take from the capture app; all speech models train on a pinned revision of it, selected by blend. Gated.", "in_blends": [ "cs", "all" ], "status": "published", "url": "https://huggingface.co/datasets/danielrosehill/Read-Aloud-Voice-Sentences", "last_modified": "2026-10-27" }, { "id": "danielrosehill/English-Hebrew-Codeswitching-Sentences", "title": "English-Hebrew Code-Switching Sentences", "kind": "audio-takes", "tag": "code_switch", "description": "English sentences with everyday Hebrew words and Israeli names written in Latin letters, read aloud by one English speaker living in Israel", "in_blends": [ "cs", "all" ], "status": "published", "url": "https://huggingface.co/datasets/danielrosehill/English-Hebrew-Codeswitching-Sentences", "last_modified": "2026-10-27" }, { "id": "danielrosehill/Tech-Sentences", "title": "Tech Sentences", "kind": "audio-takes", "tag": "tech", "description": "Dictation-style English sentences dense in software, DevOps, cloud, self-hosting and AI vocabulary (product names, CLI tools, acronyms, model names), read aloud by one speaker", "in_blends": [ "all" ], "status": "published", "url": "https://huggingface.co/datasets/danielrosehill/Tech-Sentences", "last_modified": "2026-10-27" }, { "id": "danielrosehill/AI-Interactions-Sentences", "title": "AI Interactions Sentences", "kind": "audio-takes", "tag": "ai_interactions", "description": "Instructions dictated to AI coding agents (Claude Code, Codex and others) and the git and GitHub workflow around them, read aloud by one speaker: subagents, worktrees, compaction, plan mode, hooks, MCP servers, pull requests, rebases", "in_blends": [ "all" ], "status": "published", "url": "https://huggingface.co/datasets/danielrosehill/AI-Interactions-Sentences", "last_modified": "2026-10-27" }, { "id": "danielrosehill/Linux-Admin-Sentences", "title": "Linux Admin Sentences", "kind": "audio-takes", "tag": "linux", "description": "Dictation-style English sentences about Linux desktop and server administration (KDE Plasma, GNOME, systemd, storage, networking, homelab), read aloud by one speaker", "in_blends": [ "all" ], "status": "published", "url": "https://huggingface.co/datasets/danielrosehill/Linux-Admin-Sentences", "last_modified": "2026-10-27" }, { "id": "danielrosehill/Smart-Home-Sentences", "title": "Smart Home Sentences", "kind": "audio-takes", "tag": "smart_home", "description": "Dictation-style English sentences about home automation (Home Assistant, Zigbee, Z-Wave, Matter, Thread, ESPHome, MQTT and device brands), read aloud by one speaker", "in_blends": [ "all" ], "status": "published", "url": "https://huggingface.co/datasets/danielrosehill/Smart-Home-Sentences", "last_modified": "2026-10-27" }, { "id": "danielrosehill/Personal-Vocabulary-Sentences", "title": "Personal Vocabulary Sentences", "kind": "audio-takes", "tag": "personal", "description": "English sentences built around names a speech model gets wrong for one speaker: his own name, his company and his project names (Daniel Rosehill, DSR Holdings, Carrot Cake AI, the podcast My Weird Prompts and its hosts Corn and Herman Poppl", "in_blends": [ "all" ], "status": "published", "url": "https://huggingface.co/datasets/danielrosehill/Personal-Vocabulary-Sentences", "last_modified": "2026-10-27" }, { "id": "danielrosehill/Homophone-Context-Sentences", "title": "Homophone Context Sentences", "kind": "audio-takes", "tag": "homophone", "description": "English sentences whose context settles which spelling of a homophone is meant (their/there, principal/principle, and 58 more sets), read aloud by one speaker", "in_blends": [ "all" ], "status": "published", "url": "https://huggingface.co/datasets/danielrosehill/Homophone-Context-Sentences", "last_modified": "2026-10-27" }, { "id": "Hebrish/Yiddish-Sentences", "title": "Yiddish Sentences", "kind": "audio-takes", "tag": "yiddish", "description": "English sentences with Yiddish words written in Latin letters (shul, daven, cholent, mensch, freier, tachles), the way English speakers in Israel use them, read aloud by one speaker", "in_blends": [ "all" ], "status": "published", "url": "https://huggingface.co/datasets/Hebrish/Yiddish-Sentences", "last_modified": "2026-10-27" }, { "id": "Hebrish/Jewish-Religious-Terminology-Sentences", "title": "Jewish Religious Terminology Sentences", "kind": "audio-takes", "tag": "religious", "description": "English sentences with Jewish religious vocabulary written in Latin letters: Shabbat and the festivals, prayer and the synagogue, Torah portions, Talmud and halacha, kashrut, and life-cycle events, read aloud by one speaker", "in_blends": [ "all" ], "status": "published", "url": "https://huggingface.co/datasets/Hebrish/Jewish-Religious-Terminology-Sentences", "last_modified": "2026-10-27" }, { "id": "danielrosehill/General-English-Sentences", "title": "General English Sentences", "kind": "audio-takes", "tag": "general", "description": "Plain, everyday English sentences (emails, messages, general prose and homophone pairs) read aloud by one speaker, with no Hebrew or Yiddish words, Israeli names or tech vocabulary", "in_blends": [ "all" ], "status": "published", "url": "https://huggingface.co/datasets/danielrosehill/General-English-Sentences", "last_modified": "2026-10-27" }, { "id": "Hebrish/Noisy-Condition-Sentences", "title": "Noisy Condition Sentences", "kind": "audio-takes", "tag": "noisy", "description": "Every take from the main dataset recorded in noise, whatever its category: outdoors, in a noisy room, with traffic, other people talking, background noise or a crying baby", "in_blends": [ "all" ], "status": "published", "url": "https://huggingface.co/datasets/Hebrish/Noisy-Condition-Sentences", "last_modified": "2026-10-27" }, { "id": "Hebrish/Disfluent-Read-Sentences", "title": "Disfluent Read Sentences", "kind": "audio-takes", "tag": "disfluency", "description": "Experimental", "in_blends": [ "all" ], "status": "published", "url": "https://huggingface.co/datasets/Hebrish/Disfluent-Read-Sentences", "last_modified": "2026-10-27" }, { "id": "Hebrish/Self-Correction-Sentences", "title": "Self-Correction Sentences", "kind": "audio-takes", "tag": "self-corrections", "description": "One speaker correcting himself mid-sentence (\"send it Tuesday, no, Wednesday\")", "in_blends": [ "all" ], "status": "published", "url": "https://huggingface.co/datasets/Hebrish/Self-Correction-Sentences", "last_modified": "2026-10-27" }, { "id": "Hebrish/Spoken-Aside-Sentences", "title": "Spoken Aside Sentences", "kind": "audio-takes", "tag": "asides", "description": "One speaker dictating a sentence and, partway through, saying something to someone in the room (\"come in, Hannah\")", "in_blends": [ "all" ], "status": "published", "url": "https://huggingface.co/datasets/Hebrish/Spoken-Aside-Sentences", "last_modified": "2026-10-27" }, { "id": "Hebrish/Hard-ASR-Sentences", "title": "Hard ASR Sentences", "kind": "audio-takes", "tag": "hard-asr", "description": "English sentences speech recognition finds hard, read by one speaker: Harvard sentences (IEEE 1969, public domain), tongue twisters, homographs, garden-path sentences, rare words, dense numbers and units, unusual proper nouns", "in_blends": [ "all" ], "status": "published", "url": "https://huggingface.co/datasets/Hebrish/Hard-ASR-Sentences", "last_modified": "2026-10-27" }, { "id": "Hebrish/Brand-Name-Sentences", "title": "Brand Name Sentences", "kind": "audio-takes", "tag": "brand-names", "description": "Natural sentences with company, product, AI model and open-source project names (Anthropic, OpenRouter, Amazon Bedrock, Qwen, Kubernetes, Nginx) read by one speaker, written in each name's official form", "in_blends": [ "all" ], "status": "published", "url": "https://huggingface.co/datasets/Hebrish/Brand-Name-Sentences", "last_modified": "2026-10-27" }, { "id": "Hebrish/Acronym-Sentences", "title": "Acronym Sentences", "kind": "audio-takes", "tag": "acronyms", "description": "Natural sentences with acronyms read by one speaker, both spelled out (API, SSH, HTTPS) and said as words (NASA, JSON, YAML), each in its standard written form", "in_blends": [ "all" ], "status": "published", "url": "https://huggingface.co/datasets/Hebrish/Acronym-Sentences", "last_modified": "2026-10-27" }, { "id": "Hebrish/Irish-English-Sentences", "title": "Irish English Sentences", "kind": "audio-takes", "tag": "irish-english", "description": "Everyday sentences in Irish English read by one speaker born in Ireland: vocabulary (craic, grand, giving out, press, messages), grammar (I'm after doing it, so it is, ye), Irish-language words used in English (Taoiseach, Dáil, Gardaí, slái", "in_blends": [ "all" ], "status": "published", "url": "https://huggingface.co/datasets/Hebrish/Irish-English-Sentences", "last_modified": "2026-10-27" }, { "id": "Hebrish/Repeated-Word-Sentences", "title": "Repeated Word Sentences", "kind": "audio-takes", "tag": "repetitions", "description": "Experimental", "in_blends": [ "all" ], "status": "published", "url": "https://huggingface.co/datasets/Hebrish/Repeated-Word-Sentences", "last_modified": "2026-10-27" }, { "id": "Hebrish/Singing-Sentences", "title": "Singing Sentences", "kind": "audio-takes", "tag": "singing", "description": "Experimental", "in_blends": [ "all" ], "status": "published", "url": "https://huggingface.co/datasets/Hebrish/Singing-Sentences", "last_modified": "2026-10-27" }, { "id": "Hebrish/Weird-Voice-Sentences", "title": "Weird Voice Sentences", "kind": "audio-takes", "tag": "weird-voices", "description": "Experimental", "in_blends": [], "status": "published", "url": "https://huggingface.co/datasets/Hebrish/Weird-Voice-Sentences", "last_modified": "2026-10-27" }, { "id": "Hebrish/Currency-Sentences", "title": "Currency Sentences", "kind": "audio-takes", "tag": "currency", "description": "One speaker saying amounts of money the natural way (\"50 shekels\", \"a dollar fifty\", \"6 pounds 50\")", "in_blends": [ "cs", "all" ], "status": "published", "url": "https://huggingface.co/datasets/Hebrish/Currency-Sentences", "last_modified": "2026-10-27" }, { "id": "Hebrish/Paragraph-Dictation-Passages", "title": "Paragraph Dictation Passages", "kind": "audio-takes", "tag": "paragraphs", "description": "Experimental", "in_blends": [], "status": "planned", "url": "https://huggingface.co/datasets/Hebrish/Paragraph-Dictation-Passages" }, { "id": "Hebrish/Expanded-Acronym-Sentences", "title": "Expanded Acronym Sentences", "kind": "audio-takes", "tag": "expanded-acronyms", "description": "Chat and business shorthand said as letters by one speaker (\"by E O D\", \"F Y I\", \"I M O\") with the transcript writing it out in full (\"by end of day\", \"For your information\", \"In my opinion\")", "in_blends": [ "all" ], "status": "published", "url": "https://huggingface.co/datasets/Hebrish/Expanded-Acronym-Sentences", "last_modified": "2026-10-27" }, { "id": "Hebrish/Procurement-Sentences", "title": "Procurement Sentences", "kind": "audio-takes", "tag": "procurement", "description": "Business sentences with purchasing and trade vocabulary read by one speaker: Incoterms 2020 (EXW, FCA, FOB, CIF, DDP, …) with their named place, purchase orders, RFQs, RFPs, invoices, bills of lading, MOQs, lead times, payment terms, freigh", "in_blends": [ "all" ], "status": "planned", "url": "https://huggingface.co/datasets/Hebrish/Procurement-Sentences" }, { "id": "Hebrish/Hardware-Sentences", "title": "Hardware Sentences", "kind": "audio-takes", "tag": "hardware", "description": "Short workshop and DIY sentences with hardware vocabulary read by one speaker: electronic components (capacitors, resistors, transistors, MOSFETs, regulators), fasteners and fixings (M3 and M4 screws, standoffs, wall anchors, Torx), connect", "in_blends": [ "all" ], "status": "planned", "url": "https://huggingface.co/datasets/Hebrish/Hardware-Sentences" }, { "id": "Hebrish/Israeli-Business-Sentences", "title": "Israeli Business Sentences", "kind": "audio-takes", "tag": "israeli-businesses", "description": "Everyday English sentences naming Israeli businesses read by one speaker: banks and insurers, supermarket and electronics chains, telecoms, food brands, cafes and public services, in the Latin spelling each uses itself (Hazi Hinam, Bank Yah", "in_blends": [ "all" ], "status": "planned", "url": "https://huggingface.co/datasets/Hebrish/Israeli-Business-Sentences" }, { "id": "Hebrish/Idiom-Sentences", "title": "Idiom Sentences", "kind": "audio-takes", "tag": "idioms", "description": "Natural sentences with English idioms that speech recognition tends to spell as a sound-alike (\"free rein\", not \"free reign\"; \"toe the line\", not \"tow\"; \"piqued my interest\"), read by one speaker, written in the standard form", "in_blends": [ "all" ], "status": "planned", "url": "https://huggingface.co/datasets/Hebrish/Idiom-Sentences" }, { "id": "Hebrish/Name-Cipher-Sentences", "title": "Name Cipher Sentences", "kind": "audio-takes", "tag": "name-cipher", "description": "Experimental, a privacy (PII obfuscation) test", "in_blends": [], "status": "planned", "url": "https://huggingface.co/datasets/Hebrish/Name-Cipher-Sentences" }, { "id": "Hebrish/Numerics-Sentences", "title": "Numerics Sentences", "kind": "audio-takes", "tag": "numerics", "description": "Every kind of number that is not money, said by one speaker in a fixed way and written the way it is typed: the same number said several ways (\"thirteen hundred\", \"one thousand three hundred\" → 1,300), decimals, temperatures (written \"27 de", "in_blends": [ "all" ], "status": "planned", "url": "https://huggingface.co/datasets/Hebrish/Numerics-Sentences" }, { "id": "Hebrish/Fast-Speech-Sentences", "title": "Fast Speech Sentences", "kind": "audio-takes", "tag": "fast-speech", "description": "Robustness data", "in_blends": [ "all" ], "status": "planned", "url": "https://huggingface.co/datasets/Hebrish/Fast-Speech-Sentences" }, { "id": "Hebrish/Whispered-Sentences", "title": "Whispered Sentences", "kind": "audio-takes", "tag": "whispered", "description": "Experimental robustness data", "in_blends": [ "all" ], "status": "planned", "url": "https://huggingface.co/datasets/Hebrish/Whispered-Sentences" }, { "id": "Hebrish/Web-Address-Sentences", "title": "Web Address Sentences", "kind": "audio-takes", "tag": "web-addresses", "description": "One speaker saying web addresses aloud (\"hebrish dot app slash benchmarks\", \"h t t p s colon slash slash\", \"localhost colon three thousand\"), with the transcript writing them as typed: `hebrish.app/benchmarks`, `https://`, `localhost:3000`", "in_blends": [ "all" ], "status": "planned", "url": "https://huggingface.co/datasets/Hebrish/Web-Address-Sentences" }, { "id": "Hebrish/Spelled-Out-Sentences", "title": "Spelled-Out Sentences", "kind": "audio-takes", "tag": "spelled-out", "description": "One speaker spelling names, words and codes letter by letter in dictation (\"my surname is B R E N N A N\"), with the transcript writing the word the letters spell (`My surname is Brennan.`); codes as typed, uppercase letters and digits (`KQ7", "in_blends": [ "all" ], "status": "planned", "url": "https://huggingface.co/datasets/Hebrish/Spelled-Out-Sentences" }, { "id": "Hebrish/False-Start-Sentences", "title": "False-Start Sentences", "kind": "audio-takes", "tag": "false-starts", "description": "Experimental", "in_blends": [ "all" ], "status": "planned", "url": "https://huggingface.co/datasets/Hebrish/False-Start-Sentences" }, { "id": "Hebrish/NATO-Alphabet-Sentences", "title": "NATO Alphabet Sentences", "kind": "audio-takes", "tag": "nato-alphabet", "description": "Experimental", "in_blends": [ "all" ], "status": "planned", "url": "https://huggingface.co/datasets/Hebrish/NATO-Alphabet-Sentences" }, { "id": "Hebrish/Latin-Phrase-Sentences", "title": "Latin Phrase Sentences", "kind": "audio-takes", "tag": "latin-phrases", "description": "One speaker reading English sentences that use a Latin phrase (de facto, ad hominem, de minimis, bona fide, ad nauseam, per se, quid pro quo), with the phrase in its standard English spelling: lowercase, no italics, no hyphen (`ad hoc`, `po", "in_blends": [ "all" ], "status": "planned", "url": "https://huggingface.co/datasets/Hebrish/Latin-Phrase-Sentences" }, { "id": "Hebrish/Fragment-Sentences", "title": "Fragment Sentences", "kind": "audio-takes", "tag": "fragments", "description": "One speaker reading short and incomplete utterances, one to six words: message replies (\"Not yet.\"), single words (\"Apparently.\"), notes to self (\"Dentist, Thursday morning.\"), list items, headings, trailing clauses (\"Unless it rains.\") and", "in_blends": [ "all" ], "status": "planned", "url": "https://huggingface.co/datasets/Hebrish/Fragment-Sentences" }, { "id": "Hebrish/Entity-Dense-Sentences", "title": "Entity-Dense Sentences", "kind": "audio-takes", "tag": "entity-dense", "description": "One speaker reading sentences that pack three or more entities into one line: company and product names, people, places, amounts, percentages, dates, times and quantities, in the style of results calls, meeting recaps, itineraries, invoices", "in_blends": [ "all" ], "status": "planned", "url": "https://huggingface.co/datasets/Hebrish/Entity-Dense-Sentences" }, { "id": "Hebrish/Spoken-Punctuation-Sentences", "title": "Spoken Punctuation Sentences", "kind": "audio-takes", "tag": "spoken-punctuation", "description": "Experimental", "in_blends": [ "all" ], "status": "planned", "url": "https://huggingface.co/datasets/Hebrish/Spoken-Punctuation-Sentences" }, { "id": "Hebrish/English-Hebrew-Codeswitching-ASR-Benchmark", "kind": "benchmark", "description": "Held-out test sets (v1, v2) the models are scored on; never trained on.", "training": "never (evaluation only)", "title": "English Hebrew Codeswitching ASR Benchmark", "tag": null, "in_blends": [], "status": "published", "url": "https://huggingface.co/datasets/Hebrish/English-Hebrew-Codeswitching-ASR-Benchmark", "last_modified": "2026-10-25" }, { "id": "Hebrish/ASR-Error-List", "kind": "error-list", "description": "Words the models mishear in Daniel's own dictation, with the wrong forms; drives the capture app's priority words. Sabich v2.1 repeated its takes 3 times.", "training": "via the master dataset's priority-word takes", "title": "ASR Error List", "tag": null, "in_blends": [], "status": "published", "url": "https://huggingface.co/datasets/Hebrish/ASR-Error-List", "last_modified": "2026-10-27" }, { "id": "Hebrish/ASR-Error-Prediction", "kind": "error-list", "description": "Predicted mistranscription candidates for planning new sentences.", "training": "never", "title": "ASR Error Prediction", "tag": null, "in_blends": [], "status": "published", "url": "https://huggingface.co/datasets/Hebrish/ASR-Error-Prediction", "last_modified": "2026-10-25" }, { "id": "Hebrish/Hebrish-TTS-Voice-Recordings", "kind": "audio-takes", "description": "Clean read takes for the Meorav voice (text-to-speech), a filtered view of the capture app's voice-clone takes.", "training": "Meorav", "title": "Hebrish TTS Voice Recordings", "tag": null, "in_blends": [], "status": "published", "url": "https://huggingface.co/datasets/Hebrish/Hebrish-TTS-Voice-Recordings", "last_modified": "2026-10-22" }, { "id": "Hebrish/English-Hebrew-Mixed-Sentences", "kind": "sentence-text", "description": "The code-switching sentence bank the capture app serves (text only).", "training": "prompts for recordings, not audio", "title": "English Hebrew Mixed Sentences", "tag": null, "in_blends": [], "status": "published", "url": "https://huggingface.co/datasets/Hebrish/English-Hebrew-Mixed-Sentences", "last_modified": "2026-10-22" }, { "id": "Hebrish/hebrew-latin-code-switching", "kind": "sentence-text", "description": "Sentences with romanized Hebrew words labelled, for the token classifier.", "training": "Hebrew-Latin token classifier", "title": "hebrew latin code switching", "tag": null, "in_blends": [], "status": "published", "url": "https://huggingface.co/datasets/Hebrish/hebrew-latin-code-switching", "last_modified": "2026-10-22" }, { "id": "Hebrish/Linux-Admin-Sentence-Bank", "kind": "sentence-text", "description": "Linux administration sentence bank (text only).", "training": "prompts for recordings, not audio", "title": "Linux Admin Sentence Bank", "tag": null, "in_blends": [], "status": "published", "url": "https://huggingface.co/datasets/Hebrish/Linux-Admin-Sentence-Bank", "last_modified": "2026-10-22" }, { "id": "Hebrish/Smart-Home-Sentence-Bank", "kind": "sentence-text", "description": "Smart-home sentence bank (text only).", "training": "prompts for recordings, not audio", "title": "Smart Home Sentence Bank", "tag": null, "in_blends": [], "status": "published", "url": "https://huggingface.co/datasets/Hebrish/Smart-Home-Sentence-Bank", "last_modified": "2026-10-22" }, { "id": "Hebrish/Personal-Vocabulary-Sentence-Bank", "kind": "sentence-text", "description": "Personal vocabulary sentence bank (text only).", "training": "prompts for recordings, not audio", "title": "Personal Vocabulary Sentence Bank", "tag": null, "in_blends": [], "status": "published", "url": "https://huggingface.co/datasets/Hebrish/Personal-Vocabulary-Sentence-Bank", "last_modified": "2026-10-26" }, { "id": "Hebrish/AI-Tech-Vocabulary-Sentence-Bank", "kind": "sentence-text", "description": "AI and tech vocabulary sentence bank (text only).", "training": "prompts for recordings, not audio", "title": "AI Tech Vocabulary Sentence Bank", "tag": null, "in_blends": [], "status": "published", "url": "https://huggingface.co/datasets/Hebrish/AI-Tech-Vocabulary-Sentence-Bank", "last_modified": "2026-10-22" }, { "id": "Hebrish/Homophone-Context-Sentence-Bank", "kind": "sentence-text", "description": "Homophone-in-context sentence bank (text only).", "training": "prompts for recordings, not audio", "title": "Homophone Context Sentence Bank", "tag": null, "in_blends": [], "status": "published", "url": "https://huggingface.co/datasets/Hebrish/Homophone-Context-Sentence-Bank", "last_modified": "2026-10-22" }, { "id": "Hebrish/AI-Interactions-Sentence-Bank", "kind": "sentence-text", "description": "Sentences dictated to AI agents (text only).", "training": "prompts for recordings, not audio", "title": "AI Interactions Sentence Bank", "tag": null, "in_blends": [], "status": "published", "url": "https://huggingface.co/datasets/Hebrish/AI-Interactions-Sentence-Bank", "last_modified": "2026-10-22" }, { "id": "Hebrish/Parakeet-V2-Blend-All", "kind": "training-mix export", "description": "Export of the `all` training mix, for reproducing Sabich runs.", "training": "export of the all mix", "title": "Parakeet V2 Blend All", "tag": null, "in_blends": [], "status": "published", "url": "https://huggingface.co/datasets/Hebrish/Parakeet-V2-Blend-All", "last_modified": "2026-10-25" }, { "id": "Hebrish/Room-Tone-Annotations", "kind": "annotations", "description": "Room-tone recordings and labels for noise conditions.", "training": "not yet used", "title": "Room Tone Annotations", "tag": null, "in_blends": [], "status": "published", "url": "https://huggingface.co/datasets/Hebrish/Room-Tone-Annotations", "last_modified": "2026-10-22" }, { "id": "Hebrish/Hebrish-Ideas", "kind": "other", "description": "Ideas recorded in the capture app.", "training": "never", "title": "Hebrish Ideas", "tag": null, "in_blends": [], "status": "published", "url": "https://huggingface.co/datasets/Hebrish/Hebrish-Ideas", "last_modified": "2026-10-26" } ] }