| | |
|---|
| | | plt.savefig(plotname, bbox_inches="tight") |
|---|
| | | |
|---|
| | | def load_data(self, wav_content: Union[str, np.ndarray, List[str]], fs: int = None) -> List: |
|---|
| | | def convert_to_wav(input_path, output_path): |
|---|
| | | from pydub import AudioSegment |
|---|
| | | try: |
|---|
| | | audio = AudioSegment.from_mp3(input_path) |
|---|
| | | audio.export(output_path, format="wav") |
|---|
| | | print("音频文件为mp3格式，已转换为wav格式") |
|---|
| | | |
|---|
| | | except Exception as e: |
|---|
| | | print(f"转换失败:{e}") |
|---|
| | | |
|---|
| | | def load_wav(path: str) -> np.ndarray: |
|---|
| | | if not path.lower().endswith('.wav'): |
|---|
| | | import os |
|---|
| | | input_path = path |
|---|
| | | path = os.path.splitext(path)[0]+'.wav' |
|---|
| | | convert_to_wav(input_path,path) #将mp3格式转换成wav格式 |
|---|
| | | |
|---|
| | | waveform, _ = librosa.load(path, sr=fs) |
|---|
| | | return waveform |
|---|
| | | |
|---|
| | |
|---|
| | | self.pred_bias = config["model_conf"]["predictor_bias"] |
|---|
| | | else: |
|---|
| | | self.pred_bias = 0 |
|---|
| | | if "lang" in config: |
|---|
| | | self.language = config["lang"] |
|---|
| | | else: |
|---|
| | | self.language = None |
|---|
| | | |
|---|
| | | def __call__( |
|---|
| | | self, wav_content: Union[str, np.ndarray, List[str]], hotwords: str, **kwargs |
|---|
