Initial commit of PhoneCoach project

backend/server.py

@@ -0,0 +1,91 @@
+from fastapi import FastAPI, File, UploadFile, Form
+import uvicorn
+import os
+from fastapi.middleware.cors import CORSMiddleware
+import whisper
+import difflib
+import pronouncing
+
+app = FastAPI()
+app.add_middleware(
+    CORSMiddleware,
+    allow_origins=["*"],
+    allow_credentials=True,
+    allow_methods=["*"],
+    allow_headers=["*"],
+)
+
+
+UPLOAD_DIR = "uploads"
+os.makedirs(UPLOAD_DIR, exist_ok=True)
+
+
+model = whisper.load_model("small")
+
+def calculate_similarity(expected: str, actual: str) -> float:
+    seq = difflib.SequenceMatcher(None, expected.split(), actual.split())
+    return seq.ratio()
+
+
+def text_to_phonemes(text: str) -> str:
+    words = text.lower().split()
+    phoneme_list = []
+    for word in words:
+        phones = pronouncing.phones_for_word(word)
+        if phones:
+            phoneme_list.append(phones[0])
+        else:
+            phoneme_list.append("[UNK]")  # mark as unknown pronunciation
+    return " ".join(phoneme_list)
+
+
+def phoneme_diff(expected: str, actual: str):
+    expected_list = expected.split()
+    actual_list = actual.split()
+    diff_result = []
+    matcher = difflib.SequenceMatcher(None, expected_list, actual_list)
+
+    for opcode, i1, i2, j1, j2 in matcher.get_opcodes():
+        if opcode == "equal":
+            diff_result.extend([(p, "match") for p in expected_list[i1:i2]])
+        elif opcode == "replace":
+            diff_result.extend([(p, "mismatch") for p in expected_list[i1:i2]])
+        elif opcode == "delete":
+            diff_result.extend([(p, "missing") for p in expected_list[i1:i2]])
+        elif opcode == "insert":
+            diff_result.extend([(p, "extra") for p in actual_list[j1:j2]])
+    return diff_result
+
+@app.post("/upload")
+async def upload_audio(
+    file: UploadFile = File(...),
+    expected_text: str = Form(...)
+):
+
+    file_path = os.path.join(UPLOAD_DIR, file.filename)
+    with open(file_path, "wb") as f:
+        f.write(await file.read())
+
+
+    result = model.transcribe(file_path)
+    transcript = result["text"]
+
+    expected_phonemes = text_to_phonemes(expected_text)
+    actual_phonemes = text_to_phonemes(transcript)
+
+
+    similarity = calculate_similarity(expected_phonemes, actual_phonemes)
+    differences = phoneme_diff(expected_phonemes, actual_phonemes)
+
+    return {
+        "message": "Audio processed successfully",
+        "transcript": transcript,
+        "expected_text": expected_text,
+        "expected_phonemes": expected_phonemes,
+        "actual_phonemes": actual_phonemes,
+        "similarity_score": round(similarity, 3),
+        "phoneme_diff": differences
+    }
+
+if __name__ == "__main__":
+    uvicorn.run(app, host="0.0.0.0", port=8000)