{
 "about": "The languages the listener (Hearing your partner) is offered in. A language is ready only when we measured it on this app's own runtime at most 15 errors in 100 words (characters for Chinese, Japanese and Korean): the first 25 FLEURS test clips, through the app's own worker on WebGPU, with its voice activity detector and 1 s end-of-speech rule (tools/asr/eval). NVIDIA's published rate is kept beside ours, for reference. tools/asr/build_asr.py copies this into the catalogue; the model is told the language by its prompt slot: the one measured for the language, for every locale of it.",
 "languages": {
  "am": {
   "status": "not-yet",
   "name": "Amharic",
   "note": "The speech model was not trained to write Amharic down."
  },
  "ar": {
   "status": "ready",
   "name": "Arabic",
   "model": "nemotron-3.5-asr-streaming-0.6b",
   "slot": 7,
   "measure": "wer",
   "published": 12.55,
   "measured": 8.4,
   "source": "ours (what decides): the first 25 FLEURS test clips of ar_eg (google/fleurs@70bb2e84, CC BY 4.0) through this app's worker on onnxruntime-web 1.30.0 WebGPU (Chrome, Apple GPU), with the VAD and the 1 s end-of-speech rule as in the app, 2026-10-01 (tools/asr/eval/results-2026-10-01.json); for reference, NVIDIA's model card (nvidia/nemotron-3.5-asr-streaming-0.6b, revision ea30d66d): FLEURS test, 320 ms chunks, language given",
   "note": "In our test of 25 read-aloud passages, on this app, about 8 words in 100 came out wrong (NVIDIA's own test: about 13)."
  },
  "bn": {
   "status": "not-yet",
   "name": "Bengali",
   "note": "The speech model was not trained to write Bengali down."
  },
  "cs": {
   "status": "not-yet",
   "name": "Czech",
   "slot": 22,
   "measure": "wer",
   "published": 22.41,
   "source": "NVIDIA's model card (nvidia/nemotron-3.5-asr-streaming-0.6b, revision ea30d66d): FLEURS test, 320 ms chunks, language given",
   "note": "In NVIDIA's own test on read speech, about 22 words in 100 came out wrong: too many to rely on yet."
  },
  "da": {
   "status": "not-yet",
   "name": "Danish",
   "slot": 25,
   "measure": "wer",
   "published": 30.0,
   "source": "NVIDIA's model card (nvidia/nemotron-3.5-asr-streaming-0.6b, revision ea30d66d): FLEURS test, 320 ms chunks, language given",
   "note": "In NVIDIA's own test on read speech, about 30 words in 100 came out wrong: too many to rely on yet."
  },
  "de": {
   "status": "ready",
   "name": "German",
   "model": "nemotron-3.5-asr-streaming-0.6b",
   "slot": 9,
   "measure": "wer",
   "published": 8.83,
   "measured": 12.91,
   "source": "ours (what decides): the first 25 FLEURS test clips of de_de (google/fleurs@70bb2e84, CC BY 4.0) through this app's worker on onnxruntime-web 1.30.0 WebGPU (Chrome, Apple GPU), with the VAD and the 1 s end-of-speech rule as in the app, 2026-10-01 (tools/asr/eval/results-2026-10-01.json); for reference, NVIDIA's model card (nvidia/nemotron-3.5-asr-streaming-0.6b, revision ea30d66d): FLEURS test, 320 ms chunks, language given",
   "note": "In our test of 25 read-aloud passages, on this app, about 13 words in 100 came out wrong (NVIDIA's own test: about 9)."
  },
  "el": {
   "status": "not-yet",
   "name": "Greek",
   "note": "NVIDIA trained the speech model on it only as a start for more training; it does not write Greek down well yet."
  },
  "en": {
   "status": "ready",
   "name": "English",
   "model": "nemotron-3.5-asr-streaming-0.6b",
   "slot": 0,
   "measure": "wer",
   "published": 8.27,
   "measured": 9.78,
   "source": "ours (what decides): the first 25 FLEURS test clips of en_us (google/fleurs@70bb2e84, CC BY 4.0) through this app's worker on onnxruntime-web 1.30.0 WebGPU (Chrome, Apple GPU), with the VAD and the 1 s end-of-speech rule as in the app, 2026-10-01 (tools/asr/eval/results-2026-10-01.json); for reference, NVIDIA's model card (nvidia/nemotron-3.5-asr-streaming-0.6b, revision ea30d66d): FLEURS test, 320 ms chunks, language given",
   "note": "In our test of 25 read-aloud passages, on this app, about 10 words in 100 came out wrong (NVIDIA's own test: about 8)."
  },
  "es": {
   "status": "ready",
   "name": "Spanish",
   "model": "nemotron-3.5-asr-streaming-0.6b",
   "slot": 2,
   "measure": "wer",
   "published": 4.39,
   "measured": 4.47,
   "source": "ours (what decides): the first 25 FLEURS test clips of es_419 (google/fleurs@70bb2e84, CC BY 4.0) through this app's worker on onnxruntime-web 1.30.0 WebGPU (Chrome, Apple GPU), with the VAD and the 1 s end-of-speech rule as in the app, 2026-10-01 (tools/asr/eval/results-2026-10-01.json); for reference, NVIDIA's model card (nvidia/nemotron-3.5-asr-streaming-0.6b, revision ea30d66d): FLEURS test, 320 ms chunks, language given",
   "note": "In our test of 25 read-aloud passages, on this app, about 4 words in 100 came out wrong (NVIDIA's own test: about 4)."
  },
  "fa": {
   "status": "not-yet",
   "name": "Persian",
   "note": "The speech model was not trained to write Persian down."
  },
  "fi": {
   "status": "not-yet",
   "name": "Finnish",
   "slot": 26,
   "measure": "wer",
   "published": 20.05,
   "source": "NVIDIA's model card (nvidia/nemotron-3.5-asr-streaming-0.6b, revision ea30d66d): FLEURS test, 320 ms chunks, language given",
   "note": "In NVIDIA's own test on read speech, about 20 words in 100 came out wrong: too many to rely on yet."
  },
  "fr": {
   "status": "ready",
   "name": "French",
   "model": "nemotron-3.5-asr-streaming-0.6b",
   "slot": 8,
   "measure": "wer",
   "published": 9.79,
   "measured": 11.67,
   "source": "ours (what decides): the first 25 FLEURS test clips of fr_fr (google/fleurs@70bb2e84, CC BY 4.0) through this app's worker on onnxruntime-web 1.30.0 WebGPU (Chrome, Apple GPU), with the VAD and the 1 s end-of-speech rule as in the app, 2026-10-01 (tools/asr/eval/results-2026-10-01.json); for reference, NVIDIA's model card (nvidia/nemotron-3.5-asr-streaming-0.6b, revision ea30d66d): FLEURS test, 320 ms chunks, language given",
   "note": "In our test of 25 read-aloud passages, on this app, about 12 words in 100 came out wrong (NVIDIA's own test: about 10)."
  },
  "gu": {
   "status": "not-yet",
   "name": "Gujarati",
   "note": "The speech model was not trained to write Gujarati down."
  },
  "ha": {
   "status": "not-yet",
   "name": "Hausa",
   "note": "The speech model was not trained to write Hausa down."
  },
  "he": {
   "status": "not-yet",
   "name": "Hebrew",
   "note": "NVIDIA trained the speech model on it only as a start for more training; it does not write Hebrew down well yet."
  },
  "hi": {
   "status": "not-yet",
   "name": "Hindi",
   "slot": 6,
   "measure": "wer",
   "published": 7.41,
   "measured": 17.51,
   "source": "ours (what decides): the first 25 FLEURS test clips of hi_in (google/fleurs@70bb2e84, CC BY 4.0) through this app's worker on onnxruntime-web 1.30.0 WebGPU (Chrome, Apple GPU), with the VAD and the 1 s end-of-speech rule as in the app, 2026-10-01 (tools/asr/eval/results-2026-10-01.json); for reference, NVIDIA's model card (nvidia/nemotron-3.5-asr-streaming-0.6b, revision ea30d66d): FLEURS test, 320 ms chunks, language given",
   "note": "In our test of 25 read-aloud passages, on this app, about 18 words in 100 came out wrong: too many to rely on yet, partly because it stopped listening at a long pause between sentences (3 of 25)."
  },
  "hu": {
   "status": "not-yet",
   "name": "Hungarian",
   "slot": 23,
   "measure": "wer",
   "published": 30.92,
   "source": "NVIDIA's model card (nvidia/nemotron-3.5-asr-streaming-0.6b, revision ea30d66d): FLEURS test, 320 ms chunks, language given",
   "note": "In NVIDIA's own test on read speech, about 31 words in 100 came out wrong: too many to rely on yet."
  },
  "id": {
   "status": "not-yet",
   "name": "Indonesian",
   "note": "The speech model was not trained to write Indonesian down."
  },
  "it": {
   "status": "ready",
   "name": "Italian",
   "model": "nemotron-3.5-asr-streaming-0.6b",
   "slot": 15,
   "measure": "wer",
   "published": 4.83,
   "measured": 6.89,
   "source": "ours (what decides): the first 25 FLEURS test clips of it_it (google/fleurs@70bb2e84, CC BY 4.0) through this app's worker on onnxruntime-web 1.30.0 WebGPU (Chrome, Apple GPU), with the VAD and the 1 s end-of-speech rule as in the app, 2026-10-01 (tools/asr/eval/results-2026-10-01.json); for reference, NVIDIA's model card (nvidia/nemotron-3.5-asr-streaming-0.6b, revision ea30d66d): FLEURS test, 320 ms chunks, language given",
   "note": "In our test of 25 read-aloud passages, on this app, about 7 words in 100 came out wrong (NVIDIA's own test: about 5)."
  },
  "ja": {
   "status": "ready",
   "name": "Japanese",
   "model": "nemotron-3.5-asr-streaming-0.6b",
   "slot": 10,
   "measure": "cer",
   "published": 12.22,
   "measured": 14.61,
   "source": "ours (what decides): the first 25 FLEURS test clips of ja_jp (google/fleurs@70bb2e84, CC BY 4.0) through this app's worker on onnxruntime-web 1.30.0 WebGPU (Chrome, Apple GPU), with the VAD and the 1 s end-of-speech rule as in the app, 2026-10-01 (tools/asr/eval/results-2026-10-01.json); for reference, NVIDIA's model card (nvidia/nemotron-3.5-asr-streaming-0.6b, revision ea30d66d): FLEURS test, 320 ms chunks, language given",
   "note": "In our test of 25 read-aloud passages, on this app, about 15 characters in 100 came out wrong (NVIDIA's own test: about 12)."
  },
  "kn": {
   "status": "not-yet",
   "name": "Kannada",
   "note": "The speech model was not trained to write Kannada down."
  },
  "ko": {
   "status": "ready",
   "name": "Korean",
   "model": "nemotron-3.5-asr-streaming-0.6b",
   "slot": 14,
   "measure": "cer",
   "published": 7.27,
   "measured": 10.74,
   "source": "ours (what decides): the first 25 FLEURS test clips of ko_kr (google/fleurs@70bb2e84, CC BY 4.0) through this app's worker on onnxruntime-web 1.30.0 WebGPU (Chrome, Apple GPU), with the VAD and the 1 s end-of-speech rule as in the app, 2026-10-01 (tools/asr/eval/results-2026-10-01.json); for reference, NVIDIA's model card (nvidia/nemotron-3.5-asr-streaming-0.6b, revision ea30d66d): FLEURS test, 320 ms chunks, language given",
   "note": "In our test of 25 read-aloud passages, on this app, about 11 characters in 100 came out wrong (NVIDIA's own test: about 7)."
  },
  "ml": {
   "status": "not-yet",
   "name": "Malayalam",
   "note": "The speech model was not trained to write Malayalam down."
  },
  "mr": {
   "status": "not-yet",
   "name": "Marathi",
   "note": "The speech model was not trained to write Marathi down."
  },
  "ms": {
   "status": "not-yet",
   "name": "Malay",
   "note": "The speech model was not trained to write Malay down."
  },
  "nb": {
   "status": "not-yet",
   "name": "Norwegian",
   "slot": 103,
   "measure": "wer",
   "published": 18.9,
   "source": "NVIDIA's model card (nvidia/nemotron-3.5-asr-streaming-0.6b, revision ea30d66d): FLEURS test, 320 ms chunks, language given",
   "note": "In NVIDIA's own test on read speech, about 19 words in 100 came out wrong: too many to rely on yet."
  },
  "nl": {
   "status": "not-yet",
   "name": "Dutch",
   "slot": 16,
   "measure": "wer",
   "published": 12.17,
   "measured": 16.23,
   "source": "ours (what decides): the first 25 FLEURS test clips of nl_nl (google/fleurs@70bb2e84, CC BY 4.0) through this app's worker on onnxruntime-web 1.30.0 WebGPU (Chrome, Apple GPU), with the VAD and the 1 s end-of-speech rule as in the app, 2026-10-01 (tools/asr/eval/results-2026-10-01.json); for reference, NVIDIA's model card (nvidia/nemotron-3.5-asr-streaming-0.6b, revision ea30d66d): FLEURS test, 320 ms chunks, language given",
   "note": "In our test of 25 read-aloud passages, on this app, about 16 words in 100 came out wrong: too many to rely on yet."
  },
  "pa": {
   "status": "not-yet",
   "name": "Punjabi",
   "note": "The speech model was not trained to write Punjabi down."
  },
  "pl": {
   "status": "not-yet",
   "name": "Polish",
   "slot": 17,
   "measure": "wer",
   "published": 17.48,
   "measured": 17.36,
   "source": "ours (what decides): the first 25 FLEURS test clips of pl_pl (google/fleurs@70bb2e84, CC BY 4.0) through this app's worker on onnxruntime-web 1.30.0 WebGPU (Chrome, Apple GPU), with the VAD and the 1 s end-of-speech rule as in the app, 2026-10-01 (tools/asr/eval/results-2026-10-01.json); for reference, NVIDIA's model card (nvidia/nemotron-3.5-asr-streaming-0.6b, revision ea30d66d): FLEURS test, 320 ms chunks, language given",
   "note": "In our test of 25 read-aloud passages, on this app, about 17 words in 100 came out wrong: too many to rely on yet."
  },
  "pt": {
   "status": "ready",
   "name": "Portuguese",
   "model": "nemotron-3.5-asr-streaming-0.6b",
   "slot": 12,
   "measure": "wer",
   "published": 5.81,
   "measured": 11.43,
   "source": "ours (what decides): the first 25 FLEURS test clips of pt_br (google/fleurs@70bb2e84, CC BY 4.0) through this app's worker on onnxruntime-web 1.30.0 WebGPU (Chrome, Apple GPU), with the VAD and the 1 s end-of-speech rule as in the app, 2026-10-01 (tools/asr/eval/results-2026-10-01.json); for reference, NVIDIA's model card (nvidia/nemotron-3.5-asr-streaming-0.6b, revision ea30d66d): FLEURS test, 320 ms chunks, language given",
   "note": "In our test of 25 read-aloud passages, on this app, about 11 words in 100 came out wrong (NVIDIA's own test: about 6)."
  },
  "ro": {
   "status": "not-yet",
   "name": "Romanian",
   "slot": 20,
   "measure": "wer",
   "published": 29.04,
   "source": "NVIDIA's model card (nvidia/nemotron-3.5-asr-streaming-0.6b, revision ea30d66d): FLEURS test, 320 ms chunks, language given",
   "note": "In NVIDIA's own test on read speech, about 29 words in 100 came out wrong: too many to rely on yet."
  },
  "ru": {
   "status": "ready",
   "name": "Russian",
   "model": "nemotron-3.5-asr-streaming-0.6b",
   "slot": 11,
   "measure": "wer",
   "published": 9.87,
   "measured": 14.32,
   "source": "ours (what decides): the first 25 FLEURS test clips of ru_ru (google/fleurs@70bb2e84, CC BY 4.0) through this app's worker on onnxruntime-web 1.30.0 WebGPU (Chrome, Apple GPU), with the VAD and the 1 s end-of-speech rule as in the app, 2026-10-01 (tools/asr/eval/results-2026-10-01.json); for reference, NVIDIA's model card (nvidia/nemotron-3.5-asr-streaming-0.6b, revision ea30d66d): FLEURS test, 320 ms chunks, language given",
   "note": "In our test of 25 read-aloud passages, on this app, about 14 words in 100 came out wrong (NVIDIA's own test: about 10)."
  },
  "sv": {
   "status": "not-yet",
   "name": "Swedish",
   "slot": 24,
   "measure": "wer",
   "published": 23.63,
   "source": "NVIDIA's model card (nvidia/nemotron-3.5-asr-streaming-0.6b, revision ea30d66d): FLEURS test, 320 ms chunks, language given",
   "note": "In NVIDIA's own test on read speech, about 24 words in 100 came out wrong: too many to rely on yet."
  },
  "sw": {
   "status": "not-yet",
   "name": "Swahili",
   "note": "The speech model was not trained to write Swahili down."
  },
  "ta": {
   "status": "not-yet",
   "name": "Tamil",
   "note": "The speech model was not trained to write Tamil down."
  },
  "te": {
   "status": "not-yet",
   "name": "Telugu",
   "note": "The speech model was not trained to write Telugu down."
  },
  "th": {
   "status": "not-yet",
   "name": "Thai",
   "note": "NVIDIA trained the speech model on it only as a start for more training; it does not write Thai down well yet."
  },
  "tl": {
   "status": "not-yet",
   "name": "Filipino",
   "note": "The speech model was not trained to write Filipino down."
  },
  "tr": {
   "status": "not-yet",
   "name": "Turkish",
   "slot": 18,
   "measure": "wer",
   "published": 12.05,
   "measured": 16.19,
   "source": "ours (what decides): the first 25 FLEURS test clips of tr_tr (google/fleurs@70bb2e84, CC BY 4.0) through this app's worker on onnxruntime-web 1.30.0 WebGPU (Chrome, Apple GPU), with the VAD and the 1 s end-of-speech rule as in the app, 2026-10-01 (tools/asr/eval/results-2026-10-01.json); for reference, NVIDIA's model card (nvidia/nemotron-3.5-asr-streaming-0.6b, revision ea30d66d): FLEURS test, 320 ms chunks, language given",
   "note": "In our test of 25 read-aloud passages, on this app, about 16 words in 100 came out wrong: too many to rely on yet."
  },
  "uk": {
   "status": "ready",
   "name": "Ukrainian",
   "model": "nemotron-3.5-asr-streaming-0.6b",
   "slot": 19,
   "measure": "wer",
   "published": 14.55,
   "measured": 13.8,
   "source": "ours (what decides): the first 25 FLEURS test clips of uk_ua (google/fleurs@70bb2e84, CC BY 4.0) through this app's worker on onnxruntime-web 1.30.0 WebGPU (Chrome, Apple GPU), with the VAD and the 1 s end-of-speech rule as in the app, 2026-10-01 (tools/asr/eval/results-2026-10-01.json); for reference, NVIDIA's model card (nvidia/nemotron-3.5-asr-streaming-0.6b, revision ea30d66d): FLEURS test, 320 ms chunks, language given",
   "note": "In our test of 25 read-aloud passages, on this app, about 14 words in 100 came out wrong (NVIDIA's own test: about 15)."
  },
  "ur": {
   "status": "not-yet",
   "name": "Urdu",
   "note": "The speech model was not trained to write Urdu down."
  },
  "vi": {
   "status": "ready",
   "name": "Vietnamese",
   "model": "nemotron-3.5-asr-streaming-0.6b",
   "slot": 33,
   "measure": "wer",
   "published": 12.29,
   "measured": 14.11,
   "source": "ours (what decides): the first 25 FLEURS test clips of vi_vn (google/fleurs@70bb2e84, CC BY 4.0) through this app's worker on onnxruntime-web 1.30.0 WebGPU (Chrome, Apple GPU), with the VAD and the 1 s end-of-speech rule as in the app, 2026-10-01 (tools/asr/eval/results-2026-10-01.json); for reference, NVIDIA's model card (nvidia/nemotron-3.5-asr-streaming-0.6b, revision ea30d66d): FLEURS test, 320 ms chunks, language given",
   "note": "In our test of 25 read-aloud passages, on this app, about 14 words in 100 came out wrong (NVIDIA's own test: about 12)."
  },
  "yo": {
   "status": "not-yet",
   "name": "Yoruba",
   "note": "The speech model was not trained to write Yoruba down."
  },
  "zh": {
   "status": "not-yet",
   "name": "Chinese",
   "slot": 4,
   "measure": "cer",
   "published": 20.03,
   "source": "NVIDIA's model card (nvidia/nemotron-3.5-asr-streaming-0.6b, revision ea30d66d): FLEURS test, 320 ms chunks, language given",
   "note": "In NVIDIA's own test on read speech, about 20 characters in 100 came out wrong: too many to rely on yet."
  },
  "zu": {
   "status": "not-yet",
   "name": "Zulu",
   "note": "The speech model was not trained to write Zulu down."
  }
 }
}