Kuis terkait panduan · Mudah Tingkat
Kuis Deteksi Aktivitas Suara
Tinjau deteksi aktivitas suara, keputusan ucapan tingkat bingkai, perilaku mabuk, dan perubahan ambang batas dalam streaming audio.
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Apa tugas utama Deteksi Aktivitas Suara?
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Jawaban dan penjelasan muncul saat Anda mengikuti kuis.
- Apa tugas utama Deteksi Aktivitas Suara?
- Putuskan apakah audio berisi ucapan atau tidak
- Identifikasi siapa yang berbicara
- Terjemahkan ucapan ke dalam teks
- Hasilkan suara sintetis
- How does the OpenAI Realtime API’s server_vad mode determine audio chunks?
- By identifying the speaker’s legal name
- By using periods of silence
- By examining image frames
- By grouping words alphabetically
- What does silence_duration_ms configure in server_vad?
- The length of the speaker embedding
- Kecepatan sampel audio
- How long a silent interval is used to detect that speech has stopped
- How many words appear in a transcript
- What range does the documented server_vad activation threshold use?
- -100 to 100
- 1 to 1000
- Only the strings “low” and “high”
- 0 banding 1
- How does semantic_vad estimate that a user has finished speaking?
- It uses a semantic classifier based on the words the user has uttered
- It waits for exactly 500 milliseconds of silence only
- It checks for a camera image
- It counts speaker turns from a diarization transcript
- What does high eagerness do in semantic_vad?
- It waits longer before every response
- It chunks audio sooner and can return transcription events faster
- It disables all speech detection
- It increases the number of speakers in the audio
- What is the documented default equivalent of semantic_vad eagerness set to auto?
- Nol
- High
- Sedang
- No threshold
- Why may a streaming VAD include padding before detected speech?
- To add words that were not spoken
- To identify the real-world speaker name
- To reduce every utterance to one frame
- To preserve audio immediately preceding the detected onset