雾聪
2024-01-15 8a8d60d5786510ec7b1dd4f622e848de8a15f8a8
examples/industrial_data_pretraining/paraformer_streaming/demo.py
@@ -9,7 +9,7 @@
encoder_chunk_look_back = 4 #number of chunks to lookback for encoder self-attention
decoder_chunk_look_back = 1 #number of encoder chunks to lookback for decoder cross-attention
model = AutoModel(model="damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-online", model_revision="v2.0.0")
model = AutoModel(model="damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-online", model_revision="v2.0.2")
cache = {}
res = model(input="https://isv-data.oss-cn-hangzhou.aliyuncs.com/ics/MaaS/ASR/test_audio/asr_example_zh.wav",
            chunk_size=chunk_size,
@@ -28,10 +28,10 @@
chunk_stride = chunk_size[1] * 960 # 600ms、480ms
cache = {}
for i in range(int(len((speech)-1)/chunk_stride+1)):
total_chunk_num = int(len((speech)-1)/chunk_stride+1)
for i in range(total_chunk_num):
    speech_chunk = speech[i*chunk_stride:(i+1)*chunk_stride]
    is_final = i == int(len((speech)-1)/chunk_stride+1)
    is_final = i == total_chunk_num - 1
    res = model(input=speech_chunk,
                cache=cache,
                is_final=is_final,