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sensevoice

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游雁 2024-07-16 13:57:51 +08:00
parent f097706c40
commit 8b74979bd3
2 changed files with 70 additions and 9 deletions
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72
examples/industrial_data_pretraining/sense_voice/demo.py
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@ -3,26 +3,82 @@
# Copyright FunASR (https://github.com/alibaba-damo-academy/FunASR). All Rights Reserved.
# MIT License (https://opensource.org/licenses/MIT)
import sys
from funasr import AutoModel
from funasr.utils.postprocess_utils import rich_transcription_postprocess
model_dir = "iic/SenseVoiceSmall"
input_file = (
"https://isv-data.oss-cn-hangzhou.aliyuncs.com/ics/MaaS/ASR/test_audio/asr_example_zh.wav"
)
model = AutoModel(
model=model_dir,
vad_model="fsmn-vad",
vad_kwargs={"max_single_segment_time": 30000},
device="cpu",
)
# en
res = model.generate(
input=input_file,
input=f"{model.model_path}/example/en.mp3",
cache={},
language="auto", # "zn", "en", "yue", "ja", "ko", "nospeech"
use_itn=False,
use_itn=True,
batch_size_s=60,
merge_vad=True, #
merge_length_s=15,
)
text = rich_transcription_postprocess(res[0]["text"])
print(text)
# zh
res = model.generate(
input=f"{model.model_path}/example/zh.mp3",
cache={},
language="auto", # "zn", "en", "yue", "ja", "ko", "nospeech"
use_itn=True,
batch_size_s=60,
merge_vad=True, #
merge_length_s=15,
)
text = rich_transcription_postprocess(res[0]["text"])
print(text)
# yue
res = model.generate(
input=f"{model.model_path}/example/yue.mp3",
cache={},
language="auto", # "zn", "en", "yue", "ja", "ko", "nospeech"
use_itn=True,
batch_size_s=60,
merge_vad=True, #
merge_length_s=15,
)
text = rich_transcription_postprocess(res[0]["text"])
print(text)
# ja
res = model.generate(
input=f"{model.model_path}/example/ja.mp3",
cache={},
language="auto", # "zn", "en", "yue", "ja", "ko", "nospeech"
use_itn=True,
batch_size_s=60,
merge_vad=True, #
merge_length_s=15,
)
text = rich_transcription_postprocess(res[0]["text"])
print(text)
# ko
res = model.generate(
input=f"{model.model_path}/example/ko.mp3",
cache={},
language="auto", # "zn", "en", "yue", "ja", "ko", "nospeech"
use_itn=True,
batch_size_s=60,
merge_vad=True, #
merge_length_s=15,
)
text = rich_transcription_postprocess(res[0]["text"])
print(text)

7
funasr/auto/auto_model.py
View File

@ -339,7 +339,9 @@ class AutoModel:
# FIX(gcf): concat the vad clips for sense vocie model for better aed
if kwargs.get("merge_vad", False):
for i in range(len(res)):
res[i]["value"] = merge_vad(res[i]["value"], kwargs.get("merge_length", 15000))
res[i]["value"] = merge_vad(
res[i]["value"], kwargs.get("merge_length_s", 15) * 1000
)
# step.2 compute asr model
model = self.model
@ -380,6 +382,9 @@ class AutoModel:
if len(sorted_data) > 0 and len(sorted_data[0]) > 0:
batch_size = max(batch_size, sorted_data[0][0][1] - sorted_data[0][0][0])
if kwargs["device"] == "cpu":
batch_size = 0
beg_idx = 0
beg_asr_total = time.time()
time_speech_total_per_sample = speech_lengths / 16000