tried to fix transcibe failures

main.py

@@ -108,15 +108,8 @@ def is_azure_direct_upload_supported(file_path: Path, fmt: str) -> bool:
         ".mp3",
         ".ogg",
         ".flac",
-        ".webm",
-        ".wma",
-        ".aac",
-        ".amr",
-        ".speex",
-        ".m4a",
-        ".mp4",
     }
-    supported_formats = {"wav", "mp3", "ogg", "flac", "webm"}
+    supported_formats = {"wav", "mp3", "ogg", "flac"}
     return file_path.suffix.lower() in supported_exts or fmt in supported_formats
 
 
@@ -150,6 +143,15 @@ def _build_azure_definition() -> dict:
         },
         "profanityFilterMode": os.getenv("AZURE_SPEECH_PROFANITY_MODE", "Masked"),
     }
+    locales_raw = (
+        os.getenv("AZURE_SPEECH_LOCALES", "").strip()
+        or os.getenv("AZURE_SPEECH_LOCALE", "").strip()
+    )
+    if locales_raw:
+        locales = [item.strip() for item in locales_raw.split(",") if item.strip()]
+        if locales:
+            definition["locales"] = locales
+
     prompt = os.getenv("AZURE_SPEECH_LLM_PROMPT", "").strip()
     if prompt:
         definition["enhancedMode"]["prompt"] = [prompt]
@@ -175,7 +177,17 @@ def _encode_multipart_form(fields: dict[str, str], file_field: str, file_path: P
         body.extend(value.encode("utf-8"))
         body.extend(b"\r\n")
 
-    mime_type = "audio/wav" if file_path.suffix.lower() == ".wav" else "application/octet-stream"
+    mime_types = {
+        ".wav": "audio/wav",
+        ".mp3": "audio/mpeg",
+        ".ogg": "audio/ogg",
+        ".flac": "audio/flac",
+        ".webm": "audio/webm",
+        ".aac": "audio/aac",
+        ".m4a": "audio/mp4",
+        ".mp4": "audio/mp4",
+    }
+    mime_type = mime_types.get(file_path.suffix.lower(), "application/octet-stream")
     body.extend(f"--{boundary}\r\n".encode("utf-8"))
     body.extend(
         (
@@ -244,7 +256,16 @@ def _format_azure_transcript(result: dict) -> str:
     if merged_text:
         return f"SPRECHER: {merged_text}"
 
-    raise RuntimeError("Azure Speech lieferte kein Transkript zurück")
+    diagnostics = {
+        "durationMilliseconds": result.get("durationMilliseconds"),
+        "keys": sorted(result.keys()),
+    }
+    preview = json.dumps(result, ensure_ascii=False)[:1200]
+    raise RuntimeError(
+        "Azure Speech lieferte kein Transkript zurück. "
+        f"Diagnose={json.dumps(diagnostics, ensure_ascii=False)} "
+        f"Antwort={preview}"
+    )
 
 
 def transcribe_audio(file_path: Path) -> str: