open-standards/aac/aac-rs/tools/asr/eval/fetch_fleurs.py
Transaction Science 27118aadc8 fix(aac listener): what review found; languages offered as measured on the app
- The microphone is never left open. The wait for words (30 s) starts
  again whenever a sound with no words in it ends (the worker now says
  so), listening ends after 90 s in all, and it stops and lets the
  microphone go when the page is hidden or closed or the microphone goes
  away. No sound is kept once listening ends.
- Offered only where JSPI is (Chrome, Edge, Safari on a current iPad):
  the model is then read one tensor at a time. The asyncify build, and
  the path that read all 1.2 GB first, are gone; fit() says plainly why a
  browser without JSPI cannot run it. Vendored with ONNX Runtime's
  ThirdPartyNotices.txt (pinned like its LICENSE); revision aac2.
- Closing the sentence helper no longer cuts short the listener's first
  run after a download: unload spares it, and a stop from outside counts
  as interrupted (start it again, nothing downloaded again), not as
  failing on this device; an update keeps the one that worked.
- A model the catalogue lists under a new name is followed without a
  download; one it no longer lists is offered as an update.
- Muting while the app speaks goes by the audio clock (each block carries
  its time), and adds the output's delay to the tail.
- After a failed run (the graphics chip lost), the worker is dropped, so
  the next 🎤 starts afresh. Busy says what is busy; the runtime's own
  error text never reaches the person.
- Test hooks: the listener's timers, and whether each model is loaded.

Languages: offered only as we measured them on this app's runtime, ≤ 15
in 100. tools/asr/eval runs the first 25 FLEURS test clips of each
candidate through the app's own worker on WebGPU (the VAD and the 500 ms
rule as shipped) and counts the errors; every clip is in
eval/results-2026-10-01.json. Ready: Spanish 7.5, Arabic 9.2, Korean 10.7
(characters), French 12.4, English 12.6, Russian 14.3. Not yet:
Ukrainian, Italian, Turkish, Polish, Japanese, Dutch, German,
Portuguese, Hindi, Vietnamese, mostly because the 500 ms rule ends
listening at a pause between sentences: with a 1 s rule (measured, not
shipped) 12 would pass. NVIDIA's rates are kept for reference.

Co-Authored-By: Claude Opus 5.5 <[email protected]>
2026-10-01 22:13:32 -04:00

70 lines
2.8 KiB
Python

#!/usr/bin/env python3
"""Fetch the clips the listener's languages are measured on.
python3 tools/asr/eval/fetch_fleurs.py OUT [CODE=CONFIG ...]
The first 25 test clips (in the archive's order) of each language of FLEURS
(google/fleurs, CC BY 4.0) at a pinned revision, without downloading whole
archives: test.tar.gz is streamed and left once 25 clips listed in test.tsv
are out. Writes OUT/<code>/<file>.wav (16 kHz mono) and OUT/<code>/refs.json
(the clip ids and their raw transcriptions). With no CODE=CONFIG, every
language in LANGS. A language already fetched is left alone.
Standard library only (Python 3.9 or later).
"""
import csv
import io
import json
import os
import sys
import tarfile
import urllib.request
REV = "70bb2e84b976b7e960aa89f1c648e09c59f894dd"
BASE = f"https://huggingface.co/datasets/google/fleurs/resolve/{REV}/data"
CLIPS = 25
# The app's language → FLEURS's configuration (Spanish and Arabic: the only
# ones FLEURS has, Latin American and Egyptian).
LANGS = {
"ar": "ar_eg", "de": "de_de", "en": "en_us", "es": "es_419", "fr": "fr_fr", "hi": "hi_in", "it": "it_it",
"ja": "ja_jp", "ko": "ko_kr", "nl": "nl_nl", "pl": "pl_pl", "pt": "pt_br", "ru": "ru_ru", "tr": "tr_tr",
"uk": "uk_ua", "vi": "vi_vn",
}
def main(argv):
if len(argv) < 2:
print(__doc__, file=sys.stderr)
return 2
out_root = argv[1]
langs = dict(a.split("=") for a in argv[2:]) or LANGS
csv.field_size_limit(10**9)
for lang, cfg in langs.items():
d = os.path.join(out_root, lang)
if os.path.exists(os.path.join(d, "refs.json")):
continue
os.makedirs(d, exist_ok=True)
tsv = urllib.request.urlopen(f"{BASE}/{cfg}/test.tsv").read().decode("utf-8")
rows = {}
for r in csv.reader(io.StringIO(tsv), delimiter="\t", quoting=csv.QUOTE_NONE):
# id, file_name, raw_transcription, transcription, phonemes, num_samples, gender
rows[r[1]] = {"id": r[0], "raw": r[2], "norm": r[3], "num_samples": int(r[5]), "gender": r[6]}
got = []
with urllib.request.urlopen(f"{BASE}/{cfg}/audio/test.tar.gz") as resp, tarfile.open(fileobj=resp, mode="r|gz") as tf:
for m in tf:
name = os.path.basename(m.name)
if not m.isfile() or name not in rows:
continue
with open(os.path.join(d, name), "wb") as f:
f.write(tf.extractfile(m).read())
got.append({"file": name, **rows[name]})
if len(got) >= CLIPS:
break
with open(os.path.join(d, "refs.json"), "w", encoding="utf-8") as f:
json.dump({"source": f"google/fleurs@{REV} {cfg} test (CC-BY-4.0)", "clips": got}, f, ensure_ascii=False, indent=1)
print(lang, cfg, len(got), "clips", flush=True)
return 0
if __name__ == "__main__":
sys.exit(main(sys.argv))