adding program to app.py

app.py

@@ -1,7 +1,114 @@
 import gradio as gr
+from transformers import pipeline
+import torch
+import torchaudio
+from speechbrain.pretrained import EncoderClassifier
 
-def greet(name):
-    return "Hello " + name + "!!"
+# Set up pipe for whisper asr
+asr_pipe = pipeline(
+    "automatic-speech-recognition",
+    model="openai/whisper-base.en",
+    torch_dtype=torch.float32,
+    device="cpu",
+)
 
-demo = gr.Interface(fn=greet, inputs="text", outputs="text")
-demo.launch()
+# Set up pipe for 2 phonemic transcription models
+american_phoneme_pipe = pipeline("automatic-speech-recognition", model="vitouphy/wav2vec2-xls-r-300m-timit-phoneme")
+esl_phoneme_pipe = pipeline("automatic-speech-recognition", model="mrrubino/wav2vec2-large-xlsr-53-l2-arctic-phoneme")
+
+# Set up pipe for 2 accent classification models
+classifier = EncoderClassifier.from_hparams(source="Jzuluaga/accent-id-commonaccent_ecapa", savedir="pretrained_models/accent-id-commonaccent_ecapa")
+
+def native_accent_classifier(file):
+  out_prob, score, index, text_lab = classifier.classify_file(file)
+  return [{'accent': text_lab[0], 'score': round(score[0],2)}]
+
+def esl_accent_classifier(file):
+  esl_accent_pipe = pipeline(
+    "audio-classification",
+    model="kaysrubio/accent-id-distilhubert-finetuned-l2-arctic2"
+  )
+  audio, sr = torchaudio.load(file)  # Load audio
+  audio = torchaudio.transforms.Resample(orig_freq=sr, new_freq=16000)(audio)
+  audio = audio.squeeze().numpy()
+  result = esl_accent_pipe(audio, top_k=6)
+  return [{'accent': result[0]['label'], 'score': round(result[0]['score'],2)}]
+
+def transcribe_and_classify_speech(audio):
+  try:
+      asr_output = asr_pipe(
+        audio,
+        max_new_tokens=256,
+        chunk_length_s=30,
+        batch_size=8,
+      )["text"]
+  except Exception as e:
+    print(f"An error occurred with openai/whisper-base.en: {e}")
+    asr_output = "Error, make sure your file is in mono format"
+
+  try:
+    american_phoneme_output = american_phoneme_pipe(audio)['text']
+  except Exception as e:
+    print(f"An error occurred with wav2vec2-xls-r-300m-timit-phoneme: {e}")
+    american_phoneme_output = "Error, make sure your file is in mono format"
+
+  try:
+    esl_phoneme_output = esl_phoneme_pipe(audio)['text']
+  except Exception as e:
+    print(f"An error occurred with mrrubino/wav2vec2-large-xlsr-53-l2-arctic-phoneme: {e}")
+    esl_phoneme_output = "Error"
+
+  try:
+    native_accent_output = native_accent_classifier(audio)
+  except Exception as e:
+    print(f"An error occurred with Jzuluaga/accent-id-commonaccent_ecapa: {e}")
+    native_accent_output = [{'accent': 'Unknown-please upload single channel audio'}, {'score': .0}]
+
+  try:
+    esl_accent_output = esl_accent_classifier(audio)
+  except Exception as e:
+    print(f"An error occurred with kaysrubio/accent-id-distilhubert-finetuned-l2-arctic2: {e}")
+    esl_accent_output = [{'accent': 'Unknown-please upload single channel audio'}, {'score': .0}]
+
+  output = [
+      {'transcription': asr_output},
+      {'phonemes_native_eng': american_phoneme_output},
+      {'phonemes_eng_second_lang': esl_phoneme_output},
+      {'native_eng_country': native_accent_output},
+      {'first_lang_if_not_eng': esl_accent_output}
+  ]
+  return output
+
+demo = gr.Blocks()
+
+examples = [['chinese-american.wav'], ['mexican.wav'], ['vietnamese.wav'], ['indian.wav'], ['nigerian.wav']]
+
+mic_transcribe = gr.Interface(
+    fn=transcribe_and_classify_speech,
+    inputs=gr.Audio(sources="microphone", type="filepath"),
+    outputs=gr.components.Textbox(),
+    examples=examples,
+)
+
+file_transcribe = gr.Interface(
+    fn=transcribe_and_classify_speech,
+    inputs=gr.Audio(sources="upload", type="filepath"),
+    outputs=gr.components.Textbox(),
+    examples=examples,
+)
+
+# Launch gradio app demo
+with demo:
+  gr.TabbedInterface(
+    [mic_transcribe, file_transcribe],
+    ["Transcribe Microphone", "Transcribe Audio File"],
+  )
+
+demo.launch(debug=True)
+
+
+#def greet(name):
+#    return "Hello " + name + "!!"
+
+#demo = gr.Interface(fn=greet, inputs="text", outputs="text")
+#demo.launch()

chinese-american.wav

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:cdce1a1d3cc295e1bacc7b336a113fbb50175ac6ce9e03ec8fb56592ab485e95
+size 1922192

indian.wav

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:935aca9237f0e5301f29e7a198d703448d1b700bd17ddfc2ca41a5ea87e1aebd
+size 1929624

mexican.wav

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:c0656ce06d8b8afcf8618d398a636227abdad0c8b0310f8992ab7ce6cd30769c
+size 1949312

nigerian.wav

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:87f5b33de6ca632c5500ae9bb5bae83516e4845ae631f77bb4a91830226fdba8
+size 1937144

vietnamese.wav

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:d71e309a48614c82fcf88ad60fab5dae593e408b8226836d1283d6dde2db4418
+size 400472