def decode_files(client,
audio_paths: List[str],
model: str,
language_code: str,
sample_rate=8000,
max_alternatives=10,
raw: bool = False,
pcm: bool = False,
word_level: bool = False):
"""
Decode files using threaded requests
"""
chunked_audios = [
chunks_from_file(x,
sample_rate=sample_rate,
chunk_size=1,
raw=raw,
pcm=pcm) for x in audio_paths
]
threads = [
threading.Thread(target=transcribe_chunks_streaming,
args=(client, chunks, model, language_code,
sample_rate, max_alternatives, raw, word_level))
for chunks in chunked_audios
]
for thread in threads:
thread.start()
for thread in threads:
thread.join()
def decode_files(client,
audio_paths: List[str],
model: str,
language_code: str,
raw: bool = False):
"""
Decode files using threaded requests
"""
chunked_audios = [
chunks_from_file(x, chunk_size=random.randint(1, 3), raw=raw)
for x in audio_paths
]
threads = [
threading.Thread(target=transcribe_chunks,
args=(client, chunks, model, language_code, raw))
for chunks in chunked_audios
]
for thread in threads:
thread.start()
for thread in threads:
thread.join()
def decode_audios(audio_paths: List[str],
model: str,
language_code: str,
num_proc: int = 8,
segment_long_utt: bool = False,
raw: bool = False):
"""
Decode files using threaded requests
"""
if segment_long_utt:
segmented_audios = [
non_silent_segments_from_file(audio_file, segment_length=10)
for audio_file in audio_paths
]
chunked_segmented_audios = [[
chunks_from_audio_segment(seg, chunk_size=1, raw=raw)
for seg in segments
] for segments in segmented_audios]
args = [[(segment_chunks, model, language_code, raw)
for segment_chunks in segmented_audio]
for segmented_audio in chunked_segmented_audios]
results = []
for audio_segs in args:
with Pool(num_proc) as pool:
results.append(pool.starmap(transcribe_chunks, audio_segs))
else:
chunked_audios = [
chunks_from_file(x, chunk_size=1, raw=raw) for x in audio_paths
]
args = [(chunks, model, language_code, raw)
for chunks in chunked_audios]
with Pool(num_proc) as pool:
results = pool.starmap(transcribe_chunks, args)
results_dict = {
path: response
for path, response in list(zip(audio_paths, results))
}
return results_dict
def __init__(self, name, parent, item, client):
super().__init__(name, parent)
self.audios = [(chunks_from_file(audio_spec["file"]),
audio_spec["transcription"]) for audio_spec in item]
self.client = client
self.results = [None for _ in item]