Error list: 111 words, 217 occurrences (review 2026-10-27)

README.md

@@ -23,7 +23,7 @@ code-switching, Jerusalem). Each word here is fed back into training as a **prio
 recording app serves sentences with it first until there are enough takes of it. No transcript text,
 audio or other content of the dictations is published, only the word, the wrong forms and the model.
 
-- 110 words, 216 occurrences. Last review: 2026-10-27.
+- 111 words, 217 occurrences. Last review: 2026-10-27.
 - `models` / `model_line`: the Hebrish model that produced the error (Sabich, Shakshuka, …, with
   version); `model_rev` is the exact weights' revision, recorded from app 0.7.3. Errors from before
   the app recorded the model have none.
@@ -52,7 +52,7 @@ audio or other content of the dictations is published, only the word, the wrong
 | Nemotron | Nematron, Nementron | 3 | 13 / 11 |
 | Unsloth | Unsoft, On Sloth, Onsloth | 3 | 7 / 7 |
 | ab initio | a benissio, abenisio | 2 | 5 / 5 |
-| AliExpress | Alley, Alliance | 2 | 0 / 20 |
+| AliExpress | Alley, Alliance | 2 | 1 / 20 |
 | DeepSeek | DeepSee, DeepC | 2 | 10 / 9 |
 | disfluency | disluency, Dispuency | 2 | 5 / 5 |
 | DMARC | GMARC, Dimark | 2 | 5 / 5 |
@@ -60,7 +60,7 @@ audio or other content of the dictations is published, only the word, the wrong
 | Infisical | Infiniscal, Infinisco | 2 | 5 / 5 |
 | Jupyter | Jupiter | 2 | 10 / 10 |
 | Karpathy | Karpathi, Karpathi's | 2 | 10 / 10 |
-| MiniMax | Mini Max | 2 | 1 / 20 |
+| MiniMax | Mini Max | 2 | 2 / 20 |
 | Netanyahu | Etanyahu, Etnia | 2 | 6 / 6 |
 | ONNX | ONIX, onyx | 2 | 10 / 10 |
 | Qwen | Qwen1, quen | 2 | 12 / 11 |
@@ -68,10 +68,11 @@ audio or other content of the dictations is published, only the word, the wrong
 | series | Ceres, Siries | 2 | 5 / 5 |
 | TTS | CTS, tth | 2 | 8 / 7 |
 | Ubiquiti | ubiquity | 2 | 1 / 20 |
-| WhisperX | Whisper X, Whisper Air | 2 | 0 / 20 |
+| WhisperX | Whisper X, Whisper Air | 2 | 1 / 20 |
 | Z alias | ZALAS, Zed Elias | 2 | 5 / 5 |
 | abliteration | Obliteration | 1 | 5 / 5 |
 | agentic | agenda | 1 | 5 / 5 |
+| Ali | Alley | 1 | 0 / 20 |
 | AMD | MD | 1 | 5 / 5 |
 | APK | ABK | 1 | 6 / 6 |
 | ASR | ACR | 1 | 6 / 6 |
@@ -111,7 +112,7 @@ audio or other content of the dictations is published, only the word, the wrong
 | marking | marketing | 1 | 4 / 4 |
 | mass sender | math sender | 1 | 0 / 20 |
 | Meorav | Maorab | 1 | 16 / 11 |
-| Modbus | Mod bus | 1 | 0 / 20 |
+| Modbus | Mod bus | 1 | 1 / 20 |
 | Muse Spark | News Spark | 1 | 5 / 5 |
 | NIC | NISH | 1 | 0 / 20 |
 | nikud | ikut | 1 | 0 / 20 |

occurrences.jsonl

@@ -159,6 +159,7 @@
 {"word": "Z alias", "heard_as": "ZALAS", "model": "sabich Sabich v2.0", "model_line": "Sabich", "model_version": "v2.0", "model_rev": "eebf26d8c3f9139f6edb88e0d7a22375a0e25976", "source": "dictate", "date": "2026-10-24"}
 {"word": "Z alias", "heard_as": "Zed Elias", "model": "sabich Sabich v2.0", "model_line": "Sabich", "model_version": "v2.0", "model_rev": "eebf26d8c3f9139f6edb88e0d7a22375a0e25976", "source": "dictate", "date": "2026-10-24"}
 {"word": "8BitDo", "heard_as": "8-bit do", "model": "sabich v2.1", "model_line": "sabich", "model_version": "v2.1", "model_rev": "b6a5004bfe0d93120742ccbbe7cdfba2e960d19d", "source": "android-floating", "date": "2026-10-25"}
+{"word": "Ali", "heard_as": "Alley", "model": "sabich v2.1", "model_line": "sabich", "model_version": "v2.1", "model_rev": "b6a5004bfe0d93120742ccbbe7cdfba2e960d19d", "source": "android-floating", "date": "2026-10-25"}
 {"word": "AliExpress", "heard_as": "Alley", "model": "sabich v2.1", "model_line": "sabich", "model_version": "v2.1", "model_rev": "b6a5004bfe0d93120742ccbbe7cdfba2e960d19d", "source": "android-floating", "date": "2026-10-25"}
 {"word": "AliExpress", "heard_as": "Alliance", "model": "sabich v2.1", "model_line": "sabich", "model_version": "v2.1", "model_rev": "b6a5004bfe0d93120742ccbbe7cdfba2e960d19d", "source": "android-floating", "date": "2026-10-25"}
 {"word": "Bezeq", "heard_as": "Bezek", "model": "sabich Sabich v2.0", "model_line": "Sabich", "model_version": "v2.0", "model_rev": "eebf26d8c3f9139f6edb88e0d7a22375a0e25976", "source": "dictate", "date": "2026-10-25"}

words.jsonl

@@ -17,7 +17,7 @@
 {"word": "Nemotron", "heard_as": ["Nematron", "Nementron"], "kinds": ["tech", "ai_interactions"], "meaning": "NVIDIA's Nemotron model family (a streaming ASR model here)", "occurrences": 3, "models": ["sabich Sabich v2.0", "shakshuka Shakshuka v2.0"], "first_seen": "2026-10-22", "last_seen": "2026-10-22", "takes": 13, "target": 11, "status": "trained"}
 {"word": "Unsloth", "heard_as": ["Unsoft", "On Sloth", "Onsloth"], "kinds": ["tech", "ai_interactions"], "meaning": "fine-tuning library and platform", "occurrences": 3, "models": ["sabich Sabich v2.0"], "first_seen": "2026-10-23", "last_seen": "2026-10-23", "takes": 7, "target": 7, "status": "trained"}
 {"word": "ab initio", "heard_as": ["a benissio", "abenisio"], "kinds": ["other"], "meaning": "Latin: from the beginning", "occurrences": 2, "models": ["sabich Sabich v2.0"], "first_seen": "2026-10-24", "last_seen": "2026-10-24", "takes": 5, "target": 5, "status": "trained"}
-{"word": "AliExpress", "heard_as": ["Alley", "Alliance"], "kinds": ["other"], "meaning": "AliExpress, the online marketplace", "occurrences": 2, "models": ["sabich v2.1"], "first_seen": "2026-10-25", "last_seen": "2026-10-25", "takes": 0, "target": 20, "status": "training"}
+{"word": "AliExpress", "heard_as": ["Alley", "Alliance"], "kinds": ["other"], "meaning": "AliExpress, the online marketplace", "occurrences": 2, "models": ["sabich v2.1"], "first_seen": "2026-10-25", "last_seen": "2026-10-25", "takes": 1, "target": 20, "status": "training"}
 {"word": "DeepSeek", "heard_as": ["DeepSee", "DeepC"], "kinds": ["ai_interactions", "tech"], "meaning": "Chinese LLM provider", "occurrences": 2, "models": ["sabich Sabich v2.0"], "first_seen": "2026-10-24", "last_seen": "2026-10-25", "takes": 10, "target": 9, "status": "trained"}
 {"word": "disfluency", "heard_as": ["disluency", "Dispuency"], "kinds": ["tech"], "meaning": "fillers and false starts in speech", "occurrences": 2, "models": ["sabich Sabich v2.0"], "first_seen": "2026-10-24", "last_seen": "2026-10-24", "takes": 5, "target": 5, "status": "trained"}
 {"word": "DMARC", "heard_as": ["GMARC", "Dimark"], "kinds": ["tech"], "meaning": "Email authentication policy", "occurrences": 2, "models": ["sabich Sabich v2.0"], "first_seen": "2026-10-23", "last_seen": "2026-10-24", "takes": 5, "target": 5, "status": "trained"}
@@ -25,7 +25,7 @@
 {"word": "Infisical", "heard_as": ["Infiniscal", "Infinisco"], "kinds": ["tech"], "meaning": "secrets manager", "occurrences": 2, "models": ["sabich Sabich v2.0"], "first_seen": "2026-10-23", "last_seen": "2026-10-24", "takes": 5, "target": 5, "status": "trained"}
 {"word": "Jupyter", "heard_as": ["Jupiter"], "kinds": ["tech"], "meaning": "Open-source project behind Jupyter Notebook and JupyterLab; pronounced like the planet Jupiter", "occurrences": 2, "models": ["sabich Sabich v2.0"], "first_seen": "2026-10-22", "last_seen": "2026-10-23", "takes": 10, "target": 10, "status": "trained"}
 {"word": "Karpathy", "heard_as": ["Karpathi", "Karpathi's"], "kinds": ["name", "tech"], "meaning": "Andrej Karpathy, AI researcher and educator (ex-OpenAI, ex-Tesla AI)", "occurrences": 2, "models": ["sabich Sabich v2.0"], "first_seen": "2026-10-22", "last_seen": "2026-10-22", "takes": 10, "target": 10, "status": "trained"}
-{"word": "MiniMax", "heard_as": ["Mini Max"], "kinds": ["ai_interactions"], "meaning": "MiniMax, Chinese AI lab and model family", "occurrences": 2, "models": ["sabich v2.1"], "first_seen": "2026-10-26", "last_seen": "2026-10-26", "takes": 1, "target": 20, "status": "training"}
+{"word": "MiniMax", "heard_as": ["Mini Max"], "kinds": ["ai_interactions"], "meaning": "MiniMax, Chinese AI lab and model family", "occurrences": 2, "models": ["sabich v2.1"], "first_seen": "2026-10-26", "last_seen": "2026-10-26", "takes": 2, "target": 20, "status": "training"}
 {"word": "Netanyahu", "heard_as": ["Etanyahu", "Etnia"], "kinds": ["name", "hebrew"], "meaning": "Israeli prime minister", "occurrences": 2, "models": ["sabich Sabich v2.0"], "first_seen": "2026-10-22", "last_seen": "2026-10-22", "takes": 6, "target": 6, "status": "trained"}
 {"word": "ONNX", "heard_as": ["ONIX", "onyx"], "kinds": ["tech", "ai_interactions"], "meaning": "the Open Neural Network Exchange model format", "occurrences": 2, "models": ["sabich Sabich v2.0"], "first_seen": "2026-10-21", "last_seen": "2026-10-24", "takes": 10, "target": 10, "status": "trained"}
 {"word": "Qwen", "heard_as": ["Qwen1", "quen"], "kinds": ["tech", "ai_interactions"], "meaning": "Alibaba's Qwen model family", "occurrences": 2, "models": ["sabich Sabich v2.0", "shakshuka Shakshuka v2.0"], "first_seen": "2026-10-22", "last_seen": "2026-10-23", "takes": 12, "target": 11, "status": "trained"}
@@ -33,10 +33,11 @@
 {"word": "series", "heard_as": ["Ceres", "Siries"], "kinds": ["other"], "meaning": null, "occurrences": 2, "models": ["sabich Sabich v2.0"], "first_seen": "2026-10-24", "last_seen": "2026-10-24", "takes": 5, "target": 5, "status": "trained"}
 {"word": "TTS", "heard_as": ["CTS", "tth"], "kinds": ["tech", "ai_interactions"], "meaning": "text-to-speech", "occurrences": 2, "models": ["sabich Sabich v2.0", "sabich v2.0"], "first_seen": "2026-10-23", "last_seen": "2026-10-23", "takes": 8, "target": 7, "status": "trained"}
 {"word": "Ubiquiti", "heard_as": ["ubiquity"], "kinds": ["tech"], "meaning": "Ubiquiti, the UniFi networking brand", "occurrences": 2, "models": ["sabich v2.0"], "first_seen": "2026-10-23", "last_seen": "2026-10-23", "takes": 1, "target": 20, "status": "training"}
-{"word": "WhisperX", "heard_as": ["Whisper X", "Whisper Air"], "kinds": ["tech", "ai_interactions"], "meaning": "WhisperX, Whisper with word timestamps and alignment", "occurrences": 2, "models": ["sabich v2.1"], "first_seen": "2026-10-26", "last_seen": "2026-10-26", "takes": 0, "target": 20, "status": "training"}
+{"word": "WhisperX", "heard_as": ["Whisper X", "Whisper Air"], "kinds": ["tech", "ai_interactions"], "meaning": "WhisperX, Whisper with word timestamps and alignment", "occurrences": 2, "models": ["sabich v2.1"], "first_seen": "2026-10-26", "last_seen": "2026-10-26", "takes": 1, "target": 20, "status": "training"}
 {"word": "Z alias", "heard_as": ["ZALAS", "Zed Elias"], "kinds": ["linux"], "meaning": "zoxide shortcut to a repo", "occurrences": 2, "models": ["sabich Sabich v2.0"], "first_seen": "2026-10-24", "last_seen": "2026-10-24", "takes": 5, "target": 5, "status": "trained"}
 {"word": "abliteration", "heard_as": ["Obliteration"], "kinds": ["tech", "ai_interactions"], "meaning": "removing refusal behaviour from model weights", "occurrences": 1, "models": ["sabich Sabich v2.0"], "first_seen": "2026-10-23", "last_seen": "2026-10-23", "takes": 5, "target": 5, "status": "trained"}
 {"word": "agentic", "heard_as": ["agenda"], "kinds": ["ai_interactions"], "meaning": null, "occurrences": 1, "models": ["sabich Sabich v2.0"], "first_seen": "2026-10-24", "last_seen": "2026-10-24", "takes": 5, "target": 5, "status": "trained"}
+{"word": "Ali", "heard_as": ["Alley"], "kinds": ["other"], "meaning": "short for AliExpress, the online marketplace", "occurrences": 1, "models": ["sabich v2.1"], "first_seen": "2026-10-25", "last_seen": "2026-10-25", "takes": 0, "target": 20, "status": "training"}
 {"word": "AMD", "heard_as": ["MD"], "kinds": ["tech"], "meaning": "GPU and CPU maker", "occurrences": 1, "models": ["sabich Sabich v2.0"], "first_seen": "2026-10-23", "last_seen": "2026-10-23", "takes": 5, "target": 5, "status": "trained"}
 {"word": "APK", "heard_as": ["ABK"], "kinds": ["tech"], "meaning": "Android app package", "occurrences": 1, "models": ["sabich Sabich v2.0"], "first_seen": "2026-10-23", "last_seen": "2026-10-23", "takes": 6, "target": 6, "status": "trained"}
 {"word": "ASR", "heard_as": ["ACR"], "kinds": ["tech"], "meaning": "automatic speech recognition", "occurrences": 1, "models": ["sabich Sabich v2.0"], "first_seen": "2026-10-24", "last_seen": "2026-10-24", "takes": 6, "target": 6, "status": "trained"}
@@ -76,7 +77,7 @@
 {"word": "marking", "heard_as": ["marketing"], "kinds": ["other"], "meaning": "As in marking complete", "occurrences": 1, "models": ["sabich Sabich v2.0"], "first_seen": "2026-10-24", "last_seen": "2026-10-24", "takes": 4, "target": 4, "status": "trained"}
 {"word": "mass sender", "heard_as": ["math sender"], "kinds": ["other"], "meaning": "bulk email sender", "occurrences": 1, "models": ["sabich v2.1"], "first_seen": "2026-10-26", "last_seen": "2026-10-26", "takes": 0, "target": 20, "status": "training"}
 {"word": "Meorav", "heard_as": ["Maorab"], "kinds": ["personal", "hebrew"], "meaning": "Daniel's TTS voice-clone model; Hebrew for 'mixed'", "occurrences": 1, "models": ["sabich Sabich v2.0"], "first_seen": "2026-10-22", "last_seen": "2026-10-22", "takes": 16, "target": 11, "status": "trained"}
-{"word": "Modbus", "heard_as": ["Mod bus"], "kinds": ["tech", "smart_home"], "meaning": "Modbus, industrial/smart-home serial protocol", "occurrences": 1, "models": ["sabich v2.0"], "first_seen": "2026-10-23", "last_seen": "2026-10-23", "takes": 0, "target": 20, "status": "training"}
+{"word": "Modbus", "heard_as": ["Mod bus"], "kinds": ["tech", "smart_home"], "meaning": "Modbus, industrial/smart-home serial protocol", "occurrences": 1, "models": ["sabich v2.0"], "first_seen": "2026-10-23", "last_seen": "2026-10-23", "takes": 1, "target": 20, "status": "training"}
 {"word": "Muse Spark", "heard_as": ["News Spark"], "kinds": ["ai_interactions"], "meaning": "LLM", "occurrences": 1, "models": ["sabich Sabich v2.0"], "first_seen": "2026-10-24", "last_seen": "2026-10-24", "takes": 5, "target": 5, "status": "trained"}
 {"word": "NIC", "heard_as": ["NISH"], "kinds": ["tech"], "meaning": "network interface card", "occurrences": 1, "models": ["sabich v2.1"], "first_seen": "2026-10-26", "last_seen": "2026-10-26", "takes": 0, "target": 20, "status": "training"}
 {"word": "nikud", "heard_as": ["ikut"], "kinds": ["hebrew"], "meaning": "Hebrew vowel points", "occurrences": 1, "models": ["sabich v2.0"], "first_seen": "2026-10-23", "last_seen": "2026-10-23", "takes": 0, "target": 20, "status": "training"}