continue fixing

android/sample-app/src/main/java/cn/learningpad/oraltrainer/sample/MainActivity.kt

@@ -1208,16 +1208,29 @@ class MainActivity : Activity() {
                     "{\"sentence_index\":$it}"
                 }
                 text("segments", payload)
-                val scores = dubSegments.keys.sorted().map { index ->
+                val scores = dubSegments.keys.sorted().mapNotNull { index ->
                     latestScores[index]
-                }.filterNotNull().joinToString(",", "[", "]") { score ->
+                    ?.let { score -> index to score }
+                }.joinToString(",", "[", "]") { (index, score) ->
                     buildString {
                         append("{\"sentence_index\":")
-                        append(score.sentenceIndex)
+                        append(index)
                         if (score.overallScore != null) {
                             append(",\"overall_score\":")
                             append(score.overallScore)
                         }
+                        listOf(
+                            "content_score" to score.contentScore,
+                            "fluency_score" to score.fluencyScore,
+                            "duration_score" to score.durationScore,
+                            "pause_score" to score.pauseScore,
+                            "speech_rate_score" to score.speechRateScore,
+                        ).forEach { (name, value) ->
+                            value?.let {
+                                append(",\"$name\":")
+                                append(it)
+                            }
+                        }
                         score.recognizedText?.let { text ->
                             append(",\"recognized_text\":\"")
                             append(text.replace("\\", "\\\\").replace("\"", "\\\""))

sentence_api/main.py

@@ -432,9 +432,20 @@ def create_app(
                 audio_name = f"{uuid.uuid4().hex}{suffix}"
                 audio_path = service_settings.dub_shares_dir / audio_name
                 await run_in_threadpool(_persist_upload, upload.file, audio_path, 50 * 1024 * 1024)
-                await run_in_threadpool(_trim_leading_silence, audio_path)
+                await run_in_threadpool(_align_share_audio, audio_path, boundary.end_ms / 1000, moss)
                 saved_files.append(audio_path)
                 score = scores_by_index.get(sentence_index, {})
+                score_details = {
+                    key: float(score[key])
+                    for key in (
+                        "content_score",
+                        "fluency_score",
+                        "duration_score",
+                        "pause_score",
+                        "speech_rate_score",
+                    )
+                    if score.get(key) is not None
+                }
                 prepared_segments.append({
                     "sentence_index": sentence_index,
                     "start_ms": boundary.start_ms,
@@ -444,6 +455,7 @@ def create_app(
                     "audio_size_bytes": audio_path.stat().st_size,
                     "overall_score": float(score.get("overall_score", 0)),
                     "recognized_text": str(score.get("recognized_text") or ""),
+                    "score_details": json.dumps(score_details, ensure_ascii=False),
                 })
             share = video_repository.create_dub_share(
                 video_hash=video_hash.lower(),
@@ -485,6 +497,7 @@ def create_app(
                     "text": row["text"],
                     "overall_score": row["overall_score"],
                     "recognized_text": row["recognized_text"],
+                    "score_details": json.loads(row["score_details"] or "{}"),
                     "audio_url": f"/api/v1/dub-shares/{share_id}/audio/{row['audio_filename']}",
                 }
                 for row in share["segments"]
@@ -540,32 +553,73 @@ def _persist_upload(source: BinaryIO, destination: Path, max_bytes: int) -> tupl
     return digest.hexdigest(), size
 
 
-def _trim_leading_silence(audio_path: Path) -> None:
+def _align_share_audio(audio_path: Path, target_seconds: float, transcriber: Transcriber) -> None:
     ffmpeg = shutil.which("ffmpeg")
     if ffmpeg is None:
         return
-    trimmed_path = audio_path.with_name(f"{audio_path.stem}-trimmed{audio_path.suffix}")
+    aligned_path = audio_path.with_name(f"{audio_path.stem}-aligned{audio_path.suffix}")
-    command = [
-        ffmpeg,
-        "-hide_banner",
-        "-loglevel",
-        "error",
-        "-y",
-        "-i",
-        str(audio_path),
-        "-af",
-        "silenceremove=start_periods=1:start_threshold=-45dB:start_silence=0.08",
-        "-c:a",
-        "aac",
-        str(trimmed_path),
-    ]
     try:
+        transcript = transcriber.transcribe(audio_path)
+        speech_segments = [segment for segment in transcript.segments if segment.text.strip()]
+        if not speech_segments:
+            return
+        start_seconds = max(0.0, min(segment.start_seconds for segment in speech_segments) - 0.05)
+        end_seconds = min(
+            _media_duration_seconds(audio_path),
+            max(segment.end_seconds for segment in speech_segments) + 0.08,
+        )
+        if end_seconds <= start_seconds + 0.1:
+            return
+
+        filters: List[str] = [
+            "silenceremove=start_periods=1:start_threshold=-45dB:start_silence=0.03"
+        ]
+        if target_seconds > 0.2:
+            speed_factor = (end_seconds - start_seconds) / target_seconds
+            if 0.5 <= speed_factor <= 2.0:
+                filters.append(f"atempo={speed_factor:.6f}")
+
+        command = [
+            ffmpeg,
+            "-hide_banner",
+            "-loglevel",
+            "error",
+            "-y",
+            "-ss",
+            f"{start_seconds:.3f}",
+            "-t",
+            f"{end_seconds - start_seconds:.3f}",
+            "-i",
+            str(audio_path),
+            "-af",
+            ",".join(filters),
+            "-c:a",
+            "aac",
+            str(aligned_path),
+        ]
         subprocess.run(command, check=True)
-        if trimmed_path.stat().st_size == 0:
+        if aligned_path.stat().st_size > 0:
-            raise RuntimeError("Trimmed audio is empty.")
+            aligned_path.replace(audio_path)
-        trimmed_path.replace(audio_path)
+    except Exception:
-    except (OSError, subprocess.SubprocessError):
+        logger.warning("Could not align share audio %s; keeping original.", audio_path.name, exc_info=True)
-        trimmed_path.unlink(missing_ok=True)
+    finally:
+        aligned_path.unlink(missing_ok=True)
+
+
+def _media_duration_seconds(audio_path: Path) -> float:
+    ffprobe = shutil.which("ffprobe")
+    if ffprobe is None:
+        return 0.0
+    try:
+        completed = subprocess.run(
+            [ffprobe, "-v", "error", "-show_entries", "format=duration", "-of", "csv=p=0", str(audio_path)],
+            check=True,
+            capture_output=True,
+            text=True,
+        )
+        return float(completed.stdout.strip())
+    except (OSError, ValueError, subprocess.SubprocessError):
+        return 0.0
 
 
 async def _persist_request_stream(

sentence_api/repository.py

@@ -88,6 +88,7 @@ class VideoRepository:
                     audio_size_bytes INTEGER NOT NULL,
                     overall_score REAL NOT NULL DEFAULT 0,
                     recognized_text TEXT NOT NULL DEFAULT '',
+                    score_details TEXT NOT NULL DEFAULT '{}',
                     FOREIGN KEY (share_id) REFERENCES dub_shares(share_id) ON DELETE CASCADE,
                     UNIQUE (share_id, sentence_index)
                 );
@@ -107,6 +108,10 @@ class VideoRepository:
                 connection.execute(
                     "ALTER TABLE dub_share_segments ADD COLUMN recognized_text TEXT NOT NULL DEFAULT ''"
                 )
+            if "score_details" not in columns:
+                connection.execute(
+                    "ALTER TABLE dub_share_segments ADD COLUMN score_details TEXT NOT NULL DEFAULT '{}'"
+                )
 
     def upsert_upload(
         self,
@@ -328,8 +333,9 @@ class VideoRepository:
                 """
                 INSERT INTO dub_share_segments (
                     share_id, sentence_index, start_ms, end_ms, text,
-                    audio_filename, audio_size_bytes, overall_score, recognized_text
+                    audio_filename, audio_size_bytes, overall_score, recognized_text,
-                ) VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?)
+                    score_details
+                ) VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?)
                 """,
                 [
                     (
@@ -342,6 +348,7 @@ class VideoRepository:
                         segment["audio_size_bytes"],
                         segment.get("overall_score", 0),
                         segment.get("recognized_text", ""),
+                        segment.get("score_details", "{}"),
                     )
                     for segment in segments
                 ],

sentence_api/static/dub-share.html

@@ -17,7 +17,7 @@ button{flex:1;height:44px;border:0;border-radius:10px;color:#fff;background:#256
 .selected-sentence{background:#334155;color:#fff}
 .score{margin-top:6px;font-size:12px;color:#94a3b8}
 .score.good{color:#14b8a6}.score.low{color:#f97316}
-.footer{margin-top:16px;font-size:13px;color:#94a3b8}
+.footer{margin:16px auto 0;max-width:900px;padding:12px;border-radius:10px;background:#1c2228;font-size:13px;color:#cbd5e1;line-height:1.5}
 .footer a{color:#60a5fa;text-decoration:none}
 </style>
 
@@ -134,7 +134,17 @@ async function load() {
       };
       const score = document.createElement('div');
       score.className = 'score' + (item.overall_score >= 80 ? ' good' : item.overall_score && item.overall_score < 60 ? ' low' : '');
+      const details = item.score_details || {};
       score.textContent = `总分 ${Number(item.overall_score || 0).toFixed(1)}`;
+      [
+        ['内容分', details.content_score],
+        ['流畅度', details.fluency_score],
+        ['时长分', details.duration_score],
+        ['停顿分', details.pause_score],
+        ['语速分', details.speech_rate_score],
+      ].forEach(([label, value]) => {
+        if (value != null) score.textContent += ` · ${label} ${Number(value).toFixed(1)}`;
+      });
       if (item.recognized_text) score.textContent += ` · 识别：${item.recognized_text}`;
       node.appendChild(score);
       sentenceList.appendChild(node);
@@ -151,4 +161,4 @@ async function load() {
 }
 load();
 </script>
-<p class="footer">了解更多或下载跟读App：<a href="https://www.pgyer.com/genduchong" target="_blank" rel="noopener">www.pgyer.com/genduchong</a></p>
+<div class="wrap"><p class="footer">八哥口语，让您一句一句背诵，三个月掌握一门地道外语 <a href="https://www.pgyer.com/genduchong" target="_blank" rel="noopener">欢迎下载体验</a></p></div>

sentence_api/tests/test_assessment_api.py

@@ -1,5 +1,8 @@
 import io
 import json
+from pathlib import Path
+import subprocess
+from unittest import mock
 import wave
 from dataclasses import replace
 
@@ -20,6 +23,9 @@ VIDEO_HASH = "c" * 64
 class FakeTranscriber:
     available = True
 
+    def __init__(self, segments=None):
+        self.segments = segments or []
+
     def transcribe(self, audio_path, language=None):
         return Transcript(text="The meeting starts at nine.", segments=[])
 
@@ -37,7 +43,7 @@ def make_wav() -> bytes:
     return output.getvalue()
 
 
-def make_client(tmp_path, client_api_key=""):
+def make_client(tmp_path, client_api_key="", transcriber=None):
     legacy_path = tmp_path / "legacy.json"
     legacy_path.write_text(json.dumps({"videos": {}}), encoding="utf-8")
     settings = replace(
@@ -82,7 +88,7 @@ def make_client(tmp_path, client_api_key=""):
         BoundaryStore(legacy_path),
         settings=settings,
         repository=repository,
-        transcriber=FakeTranscriber(),
+        transcriber=transcriber or FakeTranscriber(),
     )
     return TestClient(app)
 
@@ -148,6 +154,54 @@ def test_get_dub_share_includes_video_hash(tmp_path):
     assert response.json()["video_hash"] == VIDEO_HASH
 
 
+def test_create_dub_share_aligns_audio_with_whisper_boundaries(tmp_path):
+    from sentence_api.transcription import Transcript, TranscriptionSegment
+    from types import SimpleNamespace
+
+    aligned = tmp_path / "aligned.wav"
+    aligned.write_bytes(b"aligned")
+    calls = []
+
+    class AlignedFakeTranscriber(FakeTranscriber):
+        available = True
+
+        def transcribe(self, audio_path, language=None):
+            calls.append(audio_path)
+            return Transcript(
+                text="The meeting starts at nine.",
+                segments=[
+                    TranscriptionSegment(
+                        start_seconds=0.4,
+                        end_seconds=1.6,
+                        text="The meeting starts at nine.",
+                    )
+                ],
+            )
+
+    client = make_client(tmp_path, transcriber=AlignedFakeTranscriber())
+    original_run = subprocess.run
+
+    def fake_run(command, **kwargs):
+        Path(command[-1]).write_bytes(b"aligned-audio")
+        return SimpleNamespace(returncode=0)
+
+    with mock.patch("sentence_api.main.subprocess.run", side_effect=fake_run), mock.patch(
+        "sentence_api.main._media_duration_seconds",
+        return_value=2.0,
+    ):
+        response = client.post(
+            "/api/v1/dub-shares",
+            data={
+                "video_hash": VIDEO_HASH,
+                "segments": json.dumps([{"sentence_index": 0}]),
+            },
+            files={"files": ("dub.wav", make_wav(), "audio/wav")},
+        )
+
+    assert response.status_code == 201, response.text
+    assert calls[0].read_bytes() == b"aligned-audio"
+
+
 def test_assessment_client_key_is_enforced_when_configured(tmp_path):
     client = make_client(tmp_path, client_api_key="tablet-key")
     endpoint = f"/api/v1/videos/{VIDEO_HASH}/sentences/0/assessments"