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README.md

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+---
+title: Wave2Vec Kyrgyz
+emoji: 😻
+colorFrom: green
+colorTo: pink
+sdk: gradio
+sdk_version: 4.32.2
+app_file: app.py
+pinned: false
+license: apache-2.0
+---
+
+Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

app.py

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+import gradio as gr
+import torch
+import torchaudio
+from transformers import Wav2Vec2ForCTC, Wav2Vec2Processor
+import librosa
+import numpy as np
+import re
+
+processor = Wav2Vec2Processor.from_pretrained("the-cramer-project/Wav2vec-Kyrgyz")
+model = Wav2Vec2ForCTC.from_pretrained("the-cramer-project/Wav2vec-Kyrgyz")
+# model.to("cuda")
+
+def transcribe(file_):
+    arr_audio, _ = librosa.load(file_, sr=16000)
+    inputs = processor(arr_audio, sampling_rate=16_000, return_tensors="pt", padding=True)
+
+    with torch.no_grad():
+        logits = model(inputs.input_values, attention_mask=inputs.attention_mask).logits
+
+    pred_ids = torch.argmax(logits, dim=-1)
+    text = processor.batch_decode(pred_ids)[0]
+    return text
+
+
+
+
+iface = gr.Interface(
+    fn=transcribe, 
+    inputs=gr.Audio(type="filepath"),
+    outputs="text",
+    title="Wave2Vec Kyrgyz",
+    description="Realtime demo for Kyrgyz speech recognition using a wave2vec model.",
+)
+
+iface.launch()
+

requirements.txt

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+gradio
+torch
+torchaudio
+transformers
+librosa
+numpy