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Datasets:
danielrosehill
/
Tech-Sentences

Tasks:
Automatic Speech Recognition
Languages:
English
Size:
n<1K
Tags:
speech
asr
fine-tuning
single-speaker
tech-vocabulary
developer
License:
Dataset card Files
xet
 Community
danielrosehill commited on
Commit
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1 Parent(s): 6142040

Sync 50 recordings from danielrosehill/Read-Aloud-Voice-Sentences

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README.md ADDED
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+ ---
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+ license: cc-by-4.0
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+ language:
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+ - en
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+ task_categories:
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+ - automatic-speech-recognition
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+ pretty_name: Tech Sentences
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+ tags:
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+ - speech
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+ - asr
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+ - fine-tuning
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+ - single-speaker
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+ - tech-vocabulary
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+ - developer
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+ - ai
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+ size_categories:
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+ - n<1K
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+ configs:
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+ - config_name: default
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+ data_files:
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+ - split: train
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+ path: data/train/**
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+ - split: test
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+ path: data/test/**
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+ ---
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+
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+ # Tech Sentences
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+
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+ 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. Terms use the vendor's own casing (GitHub, PostgreSQL, kubectl). Includes long-form dictation of instructions to AI coding agents.
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+
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+ **This is a subset of [`danielrosehill/Read-Aloud-Voice-Sentences`](https://huggingface.co/datasets/danielrosehill/Read-Aloud-Voice-Sentences)**, the full, undifferentiated
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+ dataset. It contains every phone recording there whose `categories` include `tech`. Rows are copied
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+ unchanged, with the same ids, columns and train/test split, by `scripts/sync_subsets.py` in the
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+ project repository. Do not edit this dataset directly: fix the row in the main dataset and re-sync.
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+ The subset grows as new takes are published.
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+
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+ All audio was recorded on a **OnePlus Nord 3 5G** phone using its **internal microphone**, with browser echo cancellation, noise suppression and auto gain turned off.
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+
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+ Currently: 43 train and 7 test recordings.
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+
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+ ## Layout
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+
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+ ```
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+ data/train/audio/<id>.wav 16 kHz mono 16-bit PCM
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+ data/train/metadata.jsonl
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+ data/test/... held-out set, never trained on
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+ ```
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+
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+ The `test` split is **term-disjoint**: a held-out term never appears in `train`.
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+ `load_dataset("danielrosehill/Tech-Sentences")` works directly.
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+
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+ ## Columns
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+
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+ The columns are the same as in the main dataset: `text` (ground truth, punctuated and cased like
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+ Parakeet v2 output), `categories`, `target_terms`, `prompt_source`, `edited`, `duration_s`,
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+ `environment`, `conditions`, `device` and `recorded_at`. The main dataset's card describes them.
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+
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+ ## Licence
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+
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+ CC-BY-4.0, with sentence-text attribution per `prompt_source` as described in the
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+ [main dataset's licence section](https://huggingface.co/datasets/danielrosehill/Read-Aloud-Voice-Sentences#licence-and-attribution).
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+ {"file_name": "audio/20261014T195952Z_0bd6m9.wav", "id": "20261014T195952Z_0bd6m9", "text": "I'll finish the TOML config cleanup right after Shacharit tomorrow, so you can review it before the standup, okay?", "duration_s": 8.342, "categories": ["tech", "code_switch"], "target_terms": ["Shacharit", "TOML"], "prompt_id": "p_9bb63ec96d", "prompt_source": "generated:anthropic/claude-sonnet-5.5", "mode": "bank", "edited": false, "device": "OnePlus Nord 3 5G", "environment": "quiet-indoor", "conditions": [], "sample_rate": 16000, "recorded_at": "2026-10-14T19:59:52.045Z"}
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+ {"file_name": "audio/20261014T200851Z_0bjm0m.wav", "id": "20261014T200851Z_0bjm0m", "text": "Please SSH into the Proxmox host and check which virtual machines are using the most memory, then summarise it for me before changing anything.", "duration_s": 10.102, "categories": ["tech"], "target_terms": ["Proxmox"], "prompt_id": "p_fc8cd04c3a", "prompt_source": "generated:anthropic/claude-sonnet-5.5", "mode": "bank", "edited": false, "device": "OnePlus Nord 3 5G", "environment": "quiet-indoor", "conditions": [], "sample_rate": 16000, "recorded_at": "2026-10-14T20:08:51.804Z"}
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+ {"file_name": "audio/20261014T201121Z_hsj3bw.wav", "id": "20261014T201121Z_hsj3bw", "text": "I pushed the new RAG pipeline to GitHub this morning, so can you take a look at the retrieval part before lunch?", "duration_s": 7.398, "categories": ["tech"], "target_terms": ["RAG", "GitHub"], "prompt_id": "p_53262462c5", "prompt_source": "generated:anthropic/claude-sonnet-5.5", "mode": "bank", "edited": false, "device": "OnePlus Nord 3 5G", "environment": "quiet-indoor", "conditions": [], "sample_rate": 16000, "recorded_at": "2026-10-14T20:11:21.456Z"}
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+ {"file_name": "audio/20261014T202109Z_6dq8rf.wav", "id": "20261014T202109Z_6dq8rf", "text": "Don't forget to light the shamash first tonight, and tomorrow I want to try sherpa-onnx for offline speech recognition.", "duration_s": 7.43, "categories": ["tech", "code_switch"], "target_terms": ["shamash", "sherpa-onnx"], "prompt_id": "p_1cd2af8694", "prompt_source": "generated:anthropic/claude-sonnet-5.5", "mode": "bank", "edited": false, "device": "OnePlus Nord 3 5G", "environment": "quiet-indoor", "conditions": [], "sample_rate": 16000, "recorded_at": "2026-10-14T20:21:09.206Z"}
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