Rename multilingual_audio_chat.py to app.py
Browse files
multilingual_audio_chat.py → app.py
RENAMED
|
@@ -21,6 +21,12 @@ import soundfile as sf
|
|
| 21 |
import librosa
|
| 22 |
import torch
|
| 23 |
import os
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 24 |
# import torchaudio
|
| 25 |
from transformers import Wav2Vec2ForCTC, Wav2Vec2Tokenizer
|
| 26 |
from transformers import AutoModelForCTC, AutoProcessor, AutoTokenizer, AutoModelForCausalLM
|
|
@@ -230,14 +236,6 @@ def generate_text_and_display_audio(row, model, tokenizer):
|
|
| 230 |
|
| 231 |
# In[16]:
|
| 232 |
|
| 233 |
-
|
| 234 |
-
import soundfile as sf
|
| 235 |
-
import librosa
|
| 236 |
-
import noisereduce as nr
|
| 237 |
-
import numpy as np
|
| 238 |
-
import gradio as gr
|
| 239 |
-
import pyloudnorm as pyln
|
| 240 |
-
|
| 241 |
def spectral_subtraction(audio_data, sample_rate):
|
| 242 |
# Compute short-time Fourier transform (STFT)
|
| 243 |
stft = librosa.stft(audio_data)
|
|
|
|
| 21 |
import librosa
|
| 22 |
import torch
|
| 23 |
import os
|
| 24 |
+
import soundfile as sf
|
| 25 |
+
import librosa
|
| 26 |
+
import noisereduce as nr
|
| 27 |
+
import numpy as np
|
| 28 |
+
import gradio as gr
|
| 29 |
+
import pyloudnorm as pyln
|
| 30 |
# import torchaudio
|
| 31 |
from transformers import Wav2Vec2ForCTC, Wav2Vec2Tokenizer
|
| 32 |
from transformers import AutoModelForCTC, AutoProcessor, AutoTokenizer, AutoModelForCausalLM
|
|
|
|
| 236 |
|
| 237 |
# In[16]:
|
| 238 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 239 |
def spectral_subtraction(audio_data, sample_rate):
|
| 240 |
# Compute short-time Fourier transform (STFT)
|
| 241 |
stft = librosa.stft(audio_data)
|