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Prosody Modelling

Prosody modeling concerns features such as pitch, duration, energy and emphasis that shape how speech is delivered.

Teerera kugwaro iriAI-yakarondedzerwa · ~2 min

Pa peji ino2 min verenga
  1. Pfupiso
  2. Kudzika Kwakadzika
  3. Kuitwa muNyika yeChokwadi
  4. Ramangwana reProsody Modelling
  5. Kuzvishandisa
  6. Ramba Uchiongorora
  7. Mibvunzo inowanzo bvunzwa

Pfupiso

Text-to-speech systems can model these variables to produce different valid spoken realizations of the same text.

Kudzika Kwakadzika

Prosody includes pitch movement, duration, energy and stress. FastSpeech 2 models pitch, energy and duration as conditional inputs to help address the one-to-many mapping from text to speech. Research on prosody transfer shows a synthesizer can condition its output on a reference acoustic representation to reproduce aspects of the reference’s prosody, including when the reference and output speakers differ. A corpus study of 410 naturally occurring American-English yes/no questions found varied intonation contours; the most frequent nuclear contour in that corpus was a low-rise. These findings are scoped to their task, speakers and language variety.

Kuitwa muNyika yeChokwadi

Predicting phoneme duration and pitch in a text-to-speech system.

Using reference audio to condition a synthesized utterance on a target prosodic pattern.

Testing how emphasis changes focus interpretation in a spoken sentence.

Measuring question contours on a defined speech corpus rather than assuming a universal intonation rule.

Ramangwana reProsody Modelling

Evaluate synthesized prosody on target speakers, languages and discourse contexts. A contour that is common in one corpus or dialect need not be universal, and reference transfer should be assessed for both the intended delivery and speaker identity.

Kuzvishandisa

Nei zvichikosha

  • Svika uye svika. Inonatsiridza kusvikika kuburikidza nekunyora, kurondedzera, uye mazwi ekubatanidza.
  • Mutengo uye bhajeti. Zvikwata zveMedia zvinogona kutumira odhiyo yakakwenenzverwa nekukurumidza nemabhajeti madiki.
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Chenjera

  • Kushandisa izwi zvisizvo uye njodzi dzekuedzesera dzinowedzera kana chibvumirano chisipo.
  • Kururama kunogona kudonha mumitauro, mataurirwo, kana nharaunda dzine ruzha.
  • Synthetic audio inogona kukanganisa kutaura kwechokwadi isina mavara akajeka.

Matanho anotevera

  1. Wana mvumo yakajeka yekutora inzwi, kugadzira, uye kushandisa zvakare.
  2. Yedza mhando pavatauri vakasiyana uye mamiriro ekumashure.
  3. Tsanangura apo munhu anofanira kuongorora kana kubvumidza zvabuda.
  4. Label synthetic odhiyo uye chengetedza marekodhi ekuzvidavirira.

Ramba Uchiongorora

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Take the Prosody Modeling quiz

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Mibvunzo inowanzo bvunzwa

What is Prosody Modeling?

Prosody modeling concerns features such as pitch, duration, energy and emphasis that shape how speech is delivered. Text-to-speech systems can model these variables to produce different valid spoken realizations of the same text.

Ndeipi seti yezvimiro zvinonyatso tsanangura prosody mukutaura?

Prosody inoreva suprasegmental hunhu hwekutaura, inzwi (pitch), rhythm uye nguva, kushushikana, uye simba (ruzha), anokwira pamusoro pemashoko.

Mukuenzanisa prosody, iyo yakakosha frequency (F0) inomiririrei?

F0 ndiyo yakasarudzika frequency yekutaura, mwero wekudengenyeka kwezwi rakapetwa, iro ratinonzwa senzwi kana mutinhimira wezwi.

FastSpeech 2 yakavandudza sei kutonga kweprosody pamusoro pemhando dzekare?

FastSpeech 2 yakaunza dhizaini yekusiyanisa inofanotaura nguva, kukwirira, uye simba zvakajeka, ichipa yakananga uye yakagadzikana kutonga pamusoro peprosody pane kungotarisisa.

Sei kufanotaura prosody kubva pachinyorwa chete ichionekwa sedambudziko-kusvika-vazhinji?

Iwo mazwi mamwechete anogona kuendeswa nenzira dzisingaverengeki zvichienderana nechinangwa uye manzwiro, saka mamodheru anofanirwa kusarudza pakati peakawanda echokwadi ekuverenga prosodic pane komputa mhinduro imwe.

In a corpus of 410 naturally occurring American-English yes/no questions, which nuclear contour was most frequent?

The cited corpus study reports that the low-rise nuclear contour was the most frequent pattern in its sample of 410 naturally occurring American-English yes/no questions; this is not a universal rule.