python/FunASR-XL.git

			@@ -23,11 +23,10 @@
			n_mels: int = 80,
			frame_length: int = 25,
			frame_shift: int = 10,
			filter_length_min: int = -1,
			filter_length_max: float = -1,
			lfr_m: int = 1,
			lfr_n: int = 1,
			dither: float = 1.0
			dither: float = 1.0,
			**kwargs,
			) -> None:
			check_argument_types()

			@@ -43,8 +42,6 @@
			opts.mel_opts.debug_mel = False
			self.opts = opts

			self.filter_length_min = filter_length_min
			self.filter_length_max = filter_length_max
			self.lfr_m = lfr_m
			self.lfr_n = lfr_n
			self.cmvn_file = cmvn_file
			@@ -53,6 +50,7 @@
			self.cmvn = self.load_cmvn()
			self.fbank_fn = None
			self.fbank_beg_idx = 0
			self.reset_status()

			def fbank(self,
			waveform: np.ndarray) -> Tuple[np.ndarray, np.ndarray]:
			@@ -168,4 +166,25 @@
			abs_max = 2 ** (i.bits - 1)
			offset = i.min + abs_max
			array = np.frombuffer((middle_data.astype(dtype) - offset) / abs_max, dtype=np.float32)
			return array
			return array


			def test():
			path = "/nfs/zhifu.gzf/export/damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch/example/asr_example.wav"
			import librosa
			cmvn_file = "/nfs/zhifu.gzf/export/damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch/am.mvn"
			config_file = "/nfs/zhifu.gzf/export/damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch/config.yaml"
			from funasr.runtime.python.onnxruntime.rapid_paraformer.utils.utils import read_yaml
			config = read_yaml(config_file)
			waveform, _ = librosa.load(path, sr=None)
			frontend = WavFrontend(
			cmvn_file=cmvn_file,
			**config['frontend_conf'],
			)
			speech, _ = frontend.fbank_online(waveform)
			feat, feat_len = frontend.lfr_cmvn(speech)
			frontend.reset_status() # clear cache
			return feat, feat_len

			if __name__ == '__main__':
			test()