Idanwo ti o sopọ mọ itọsọna · Lile Ipele

Filterbank ati PLP Awọn ẹya adanwo

Test how log-mel filterbanks and PLP convert short speech frames into perceptually shaped features for modern speech models.

Jẹmọ itọsọna awọn ọnaFilterbank Ati Plp Awọn ẹya ara ẹrọ
Ibeere 1 ti 8

Why do speech filterbanks use mel- or Bark-spaced bands instead of uniformly spaced hertz?

Awotẹlẹ gbogbo ibeere8 ibeere

Awọn idahun ati awọn alaye han bi o ṣe n mu ibeere naa.

  1. Why do speech filterbanks use mel- or Bark-spaced bands instead of uniformly spaced hertz?
    • The scales allocate finer frequency spacing at low frequencies and coarser spacing at high frequencies, approximating aspects of hearing
    • They make files smaller only
    • They remove all background noise
    • They guarantee perfect speech recognition
  2. Kini igbesẹ asọtẹlẹ laini ni PLP ṣaṣeyọri?
    • O mu iwọn didun pọ si
    • O baamu apoowe iwoye didan ti o n mu apẹrẹ-itumọ ohun
    • O ṣe afikun reverb
    • O ṣe iyipada ohun si ọrọ taara
  3. Iru ẹya wo ni titẹ sii ti o ga julọ fun awọn awoṣe idanimọ ọrọ jinlẹ ti ode oni?
    • Awọn faili MIDI aise
    • Awọn iwe afọwọkọ ti a kọ
    • Wọle-mel filterbank awọn ẹya ara ẹrọ
    • JPEG spectrograms
  4. Bawo ni awọn MFCC ṣe yatọ si awọn ẹya ara ẹrọ log-mel filterbank aise?
    • Awọn MVCC ko lo awọn asẹ rara
    • Awọn ኤምFCC jẹ iwọn ni decibels nikan
    • Awọn ኤምFCC nilo titobi gbohungbohun
    • Awọn ኤምFCC ṣafikun iyipada cosine lati ṣe ọṣọ awọn abajade banki filterbank
  5. Ohun ti perceptual ano PLP ni wipe ipilẹ mel filterbanks se ko?
    • Ohun ti o dogba-pariwo ti tẹ ati cube-root kikankikan funmorawon
    • Awoṣe ede ti a ṣe sinu
    • Itumọ aladaaṣe
    • Sitẹrio panṣaga
  6. Why might a deep model use log-mel features or raw waveforms instead of PLP?
    • PLP jẹ arufin lati lo
    • The model can learn useful task-specific representations without every hand-designed PLP step
    • Ohun afetigbọ aise nigbagbogbo kere
    • PLP ṣiṣẹ fun orin nikan
  7. What is a typical log-mel filterbank feature for one speech frame?
    • A word-level translation
    • A single pitch label for the whole recording
    • The logarithm of spectral energy pooled through a mel-spaced filter
    • A pixel color from a spectrogram image
  8. Which order best describes the main PLP processing steps?
    • Translation, tokenization, and decoding
    • Stereo panning, reverb, and compression
    • Image segmentation followed by color correction
    • Critical-band analysis, equal-loudness weighting, loudness compression, then linear prediction