From 5358e1f10072d2c8ad7547fb82425e761b8e94f5 Mon Sep 17 00:00:00 2001
From: haoneng.lhn <haoneng.lhn@alibaba-inc.com>
Date: 星期三, 31 五月 2023 19:06:05 +0800
Subject: [PATCH] update
---
egs_modelscope/asr/paraformer/speech_paraformer_asr_nat-zh-cn-16k-common-vocab8404-online/demo.py | 37 +++++--------------------------------
1 files changed, 5 insertions(+), 32 deletions(-)
diff --git a/egs_modelscope/asr/paraformer/speech_paraformer_asr_nat-zh-cn-16k-common-vocab8404-online/demo.py b/egs_modelscope/asr/paraformer/speech_paraformer_asr_nat-zh-cn-16k-common-vocab8404-online/demo.py
index abe6640..5fa417b 100644
--- a/egs_modelscope/asr/paraformer/speech_paraformer_asr_nat-zh-cn-16k-common-vocab8404-online/demo.py
+++ b/egs_modelscope/asr/paraformer/speech_paraformer_asr_nat-zh-cn-16k-common-vocab8404-online/demo.py
@@ -1,39 +1,12 @@
-import os
-import logging
-import torch
-import soundfile
-
from modelscope.pipelines import pipeline
from modelscope.utils.constant import Tasks
-from modelscope.utils.logger import get_logger
-logger = get_logger(log_level=logging.CRITICAL)
-logger.setLevel(logging.CRITICAL)
-
-os.environ["MODELSCOPE_CACHE"] = "./"
inference_pipeline = pipeline(
task=Tasks.auto_speech_recognition,
model='damo/speech_paraformer_asr_nat-zh-cn-16k-common-vocab8404-online',
- model_revision='v1.0.4'
+ model_revision='v1.0.6',
+ mode="paraformer_fake_streaming"
)
-
-model_dir = os.path.join(os.environ["MODELSCOPE_CACHE"], "damo/speech_paraformer_asr_nat-zh-cn-16k-common-vocab8404-online")
-speech, sample_rate = soundfile.read(os.path.join(model_dir, "example/asr_example.wav"))
-speech_length = speech.shape[0]
-
-sample_offset = 0
-chunk_size = [8, 8, 4] #[5, 10, 5] 600ms, [8, 8, 4] 480ms
-stride_size = chunk_size[1] * 960
-param_dict = {"cache": dict(), "is_final": False, "chunk_size": chunk_size}
-final_result = ""
-
-for sample_offset in range(0, speech_length, min(stride_size, speech_length - sample_offset)):
- if sample_offset + stride_size >= speech_length - 1:
- stride_size = speech_length - sample_offset
- param_dict["is_final"] = True
- rec_result = inference_pipeline(audio_in=speech[sample_offset: sample_offset + stride_size],
- param_dict=param_dict)
- if len(rec_result) != 0:
- final_result += rec_result['text']
- print(rec_result)
-print(final_result.strip())
+audio_in='https://isv-data.oss-cn-hangzhou.aliyuncs.com/ics/MaaS/ASR/test_audio/asr_example_zh.wav'
+rec_result = inference_pipeline(audio_in=audio_in)
+print(rec_result)
--
Gitblit v1.9.1