Normalize an audio signal by scaling it to have values between -1 and 1. Args: audio: The input audio signal. Returns: The normalized audio signal. Examples: >>> audio = np.array([1, 2, 3, 4, 5]) >>> normalized_audio = normalize(audio) >>> float(np.max
(audio: np.ndarray)
| 150 | |
| 151 | |
| 152 | def normalize(audio: np.ndarray) -> np.ndarray: |
| 153 | """ |
| 154 | Normalize an audio signal by scaling it to have values between -1 and 1. |
| 155 | |
| 156 | Args: |
| 157 | audio: The input audio signal. |
| 158 | |
| 159 | Returns: |
| 160 | The normalized audio signal. |
| 161 | |
| 162 | Examples: |
| 163 | >>> audio = np.array([1, 2, 3, 4, 5]) |
| 164 | >>> normalized_audio = normalize(audio) |
| 165 | >>> float(np.max(normalized_audio)) |
| 166 | 1.0 |
| 167 | >>> float(np.min(normalized_audio)) |
| 168 | 0.2 |
| 169 | """ |
| 170 | # Divide the entire audio signal by the maximum absolute value |
| 171 | return audio / np.max(np.abs(audio)) |
| 172 | |
| 173 | |
| 174 | def audio_frames( |