Maswali yanayounganishwa na mwongozo · Rahisi Kiwango

Maswali ya Kutambua Shughuli za Sauti

Pitia ugunduzi wa shughuli za sauti, maamuzi ya hotuba ya kiwango cha fremu, tabia ya hang over na biashara za vizingiti katika sauti ya mtiririko.

Njia za mwongozo zinazohusianaUtambuzi wa Shughuli ya Sauti
Swali 1 ya 8

Je, kazi ya msingi ya Kutambua Shughuli za Sauti ni ipi?

Hakiki kila swali8 maswali

Majibu na maelezo huonekana unapojibu maswali.

  1. Je, kazi ya msingi ya Kutambua Shughuli za Sauti ni ipi?
    • Amua ikiwa sauti ina hotuba au la
    • Tambua ni nani anayezungumza
    • Tafsiri hotuba kuwa maandishi
    • Tengeneza sauti za syntetisk
  2. 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
  3. What does silence_duration_ms configure in server_vad?
    • The length of the speaker embedding
    • Kiwango cha sampuli ya sauti
    • How long a silent interval is used to detect that speech has stopped
    • How many words appear in a transcript
  4. What range does the documented server_vad activation threshold use?
    • -100 to 100
    • 1 to 1000
    • Only the strings “low” and “high”
    • 0 hadi 1
  5. 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
  6. 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
  7. What is the documented default equivalent of semantic_vad eagerness set to auto?
    • Sifuri
    • High
    • Kati
    • No threshold
  8. 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