Overview
Wav2Letter ndeyekupedzisira-kusvika-kumagumo yekuziva matauriro sisitimu kubva kuFacebook AI yaingoshandisa convolutional neural network, hapana kudzokorora. Zvaive nebasa sekukurumidza, imwe nzira yakapusa yakaratidza kuti CNNs chete yaigona kunyora kutaura nemakwikwi.
Wav2Letter Convolutional ASR inogara muodhiyo-AI workflows inoshandura kutaura, mimhanzi, uye ruzha rwekutaurirana, kuwanikwa, uye kugadzirwa kwenhau.
Deep Dive
Yakaunzwa neFacebook AI Tsvagiridzo muna 2016, Wav2Letter yakatyora kubva kune inodzokororwa uye HMM-yakavakirwa nzira nekutsamira chose pane convolutional neural network kumepu odhiyo zvakananga kune mavara (mavara), saka zita. Iyo yakatanga kudzidziswa neyakajairwa AutoSegCriterion (ASG) kurasikirwa, imwe nzira iri nyore kune yakajairika CTC kurasikirwa iyo yakadonhedza chiratidzo chisina chinhu uye yakateedzerwa tsamba shanduko zvakananga. Yakanyorwa muC++ ichishandisa Flashlight/ArrayFire backend, yakagadzirirwa kumhanya paPCU neGPU. Gare gare vhezheni, Wav2Letter++ uye iyo yakazara convolutional musiyano, yakayerwa kune yakakura dhataseti uye yakawana emakwikwi ekukanganisa mazwi mitengo paLibrispeech. Yayo convolution-chete dhizaini yakaita kuti ienzanise zvakanyanya uye inference-hushamwari kana ichienzaniswa neinotevedzana RNN decoder.
Technical Insight
Wav2Letter inorongedza 1D temporal convolutions pamusoro peacoustic features, nechikamu chega chega chichikudza nzvimbo yekugamuchira zvekuti stacks dzakadzika dzinotora kureba pasina kudzokorora. Nekuti convolutions inogadzira nguva dzese nhanho dzakafanana, kudzidziswa uye inference inokurumidza. Iko kurasikirwa kwekutanga kweASG kwakafanana neCTC asi kunobvisa chiratidzo chisina chinhu uye inowedzera pachena mavara-kune-tsamba ekuchinja zvibodzwa, ichigadzira iyo inonyatso patsanurika yekutevedzana dhizaini inoyananisa kusiyanisa-kureba odhiyo kune kubuda kwemavara pasina pa-frame mavara.
Mastering Wav2Letter Convolutional ASR
Wav2Letter ndeyekupedzisira-kusvika-kumagumo yekuziva matauriro sisitimu kubva kuFacebook AI yaingoshandisa convolutional neural network, hapana kudzokorora. Zvaive nebasa sekukurumidza, imwe nzira yakapusa yakaratidza kuti CNNs chete yaigona kunyora kutaura nemakwikwi. Wav2Letter Convolutional ASR inogara muodhiyo-AI workflows inoshandura kutaura, mimhanzi, uye ruzha rwekutaurirana, kuwanikwa, uye kugadzirwa kwenhau. Kuti uvake kunzwisisa kwakadzama, bata Wav2Letter Convolutional ASR semuenzaniso wekushandisa, kwete chinhu chimwe chete: tsanangura zvinodiwa, kujekesa fungidziro, uye patsanura izvo zvingaitwe nehurongwa hwakavimbika kubva kune zvichiri kuda kutonga kwenyanzvi.
Mukuita, zvikwata zvakasimba zvinoshandisa Wav2Letter Convolutional ASR zvinobata mhando, latency, uye mvumo sezvikamu zvakakosha zvakaenzana zvehurongwa hwekuendesa. Ivo vanonyora zvakajeka maitiro ebudiriro, bvunzo vachipokana ne data rechokwadi uye mafambiro ebasa, uye iterate zvichibva pane zvakacherechedzwa maitiro ekutadza kwete kuhwina-nguva imwe chete yebhenji. Apa ndipo apo kunzwisisa kwe theoretical kunoshanduka kuve kugona kwakasimba pane chigadzirwa, mutemo, uye mashandiro.
Inonatsiridza kusvikika kuburikidza nekunyora, kurondedzera, uye mazwi ekubatanidza. Panguva imwecheteyo, kusashandiswa kweIzwi zvisizvo uye njodzi dzekuedzesera dzinowedzera kana chibvumirano chisipo. Nzira yakatsiga ndeyekubatanidza kukurumidza kuyedza nekutonga: mhanyisa vatyairi vendege, tora humbowo, buritsa matanda esarudzo, uye urambe uchivandudza chengetedzo semaitiro emuenzaniso, zvinotarisirwa nemushandisi, uye zvinodikanwa zvekutonga.
Strategic Impact
Inonatsiridza kusvikika kuburikidza nekunyora, kurondedzera, uye mazwi ekubatanidza.
Inonatsiridza kusvikika kuburikidza nekunyora, kurondedzera, uye mazwi ekubatanidza. Mukutumirwa kwemhando yepamusoro, izvi zvinoshandurirwa kuita mitemo inoyerwa yekushanda, miganhu yevaridzi, uye tsika dzekudzokorora dzinodzokororwa kuitira kuti zvikwata zvikwire kuvimba pane kukwidza kusajeka.
Zvikwata zveMedia zvinogona kutumira odhiyo yakakwenenzverwa nekukurumidza nemabhajeti madiki.
Zvikwata zveMedia zvinogona kutumira odhiyo yakakwenenzverwa nekukurumidza nemabhajeti madiki. Mukutumirwa kwemhando yepamusoro, izvi zvinoshandurirwa kuita mitemo inoyerwa yekushanda, miganhu yevaridzi, uye tsika dzekudzokorora dzinodzokororwa kuitira kuti zvikwata zvikwire kuvimba pane kukwidza kusajeka.
Masisitimu anotarisana nevatengi anogona kugadzirisa kutaurirana kwekutaura pamwero mukuru.
Masisitimu anotarisana nevatengi anogona kugadzirisa kutaurirana kwekutaura pamwero mukuru. Mukutumirwa kwemhando yepamusoro, izvi zvinoshandurirwa kuita mitemo inoyerwa yekushanda, miganhu yevaridzi, uye tsika dzekudzokorora dzinodzokororwa kuitira kuti zvikwata zvikwire kuvimba pane kukwidza kusajeka.
Real-World Implementation
Chaiyo-nguva yakanyorwa uko yakaderera-latency, yakafanana inference yakakosha kupfuura mashoma mapoinzi echokwadi.
Pa-mudziyo kana CPU-yakasungwa kutaura kucherechedzwa isingakwanise kutenga inorema inodzokororwa madhikodha
Tsvagiridzo yekutanga kuenzanisa convolutional ASR inopesana neRNN uye transformer masisitimu paLibrispeech
Kushanda senheyo yeinjiniya ye Facebook's Flashlight raibhurari uye gare gare wav2vec modhi
Maitiro Ekuita
Wav2Letter Convolutional ASR mukuita
Real-time transcription uko yakaderera-latency, parallel inference yakakosha pane mashoma mapoinzi echokwadi.
Real-time transcription uko yakaderera-latency, parallel inference inonyanya kukosha kupfuura mashoma mapoinzi echokwadi Matimu anowanzo kuwana mhedzisiro iri nani kana achinge atsanangura emhando yepamusoro kumberi, chengetedza nzira yekukwira kwevanhu yemakesi emupendero, uye kuteedzera zvese zvakawanikwa zvechigadzirwa uye mutengo wekukanganisa nekufamba kwenguva.
Wav2Letter Convolutional ASR mukuita
Pa-mudziyo kana CPU-yakasungwa kutaura kucherechedzwa isingakwanise kutenga inorema inodzokororwa madhikodha.
Pa-mudziyo kana CPU-yakasungwa kutaura kucherechedzwa iyo isingakwanise inorema inodzokororwa madhikodha Matimu anowanzo kuwana mhedzisiro iri nani kana achinge atsanangura mhando yepamusoro kumberi, chengetedza nzira yekukwira kwevanhu yemakesi emupendero, uye kuteedzera zvese zvakawanikwa zvechigadzirwa uye mutengo wekukanganisa nekufamba kwenguva.
Wav2Letter Convolutional ASR mukuita
Tsvagiridzo yekutanga kuenzanisa convolutional ASR inopesana neRNN uye transformer masisitimu paLibrispeech.
Tsvagiridzo yekutanga inoenzanisa convolutional ASR inopesana neRNN uye transformer masisitimu paLibrispeech Matimu anowanzo kuwana mhedzisiro iri nani kana vatsanangura mhando yepamusoro kumberi, chengetedza nzira yekukwira kwevanhu yemakesi ekumucheto, uye kuteedzera zvese zvakawanikwa zvechigadzirwa nemitengo yekukanganisa nekufamba kwenguva.
Wav2Letter Convolutional ASR mukuita
Kushanda senheyo yeinjiniya ye Facebook's Flashlight raibhurari uye gare gare wav2vec modhi.
Kushanda senheyo yeinjiniya yeFacebook's Flashlight raibhurari uye gare gare wav2vec modhi Matimu anowanzo kuwana mhedzisiro kana atsanangura mhando yepamusoro kumberi, chengetedza nzira yekukwira kwevanhu yemakesi ekumucheto, uye kuteedzera zvese zvakawanikwa zvechigadzirwa uye mutengo wekukanganisa nekufamba kwenguva.
Njodzi & Guardrails
Kusashandisa 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.
Implementation Roadmap
Wana mvumo yakajeka yekutora inzwi, kugadzira, uye kushandisa zvakare.
Wana mvumo yakajeka yekutora inzwi, kugadzira, uye kushandisa zvakare. Bata nhanho yega yega segedhi rehumbowo: kana maitiro asina kusangana, imbomira kuburitsa, vhara gaka, uye wobva wawedzera kushandiswa.
Yedza mhando pavatauri vakasiyana uye mamiriro ekumashure.
Yedza mhando pavatauri vakasiyana uye mamiriro ekumashure. Bata nhanho yega yega segedhi rehumbowo: kana maitiro asina kusangana, imbomira kuburitsa, vhara gaka, uye wobva wawedzera kushandiswa.
Tsanangura apo munhu anofanira kuongorora kana kubvumidza zvabuda.
Tsanangura apo munhu anofanira kuongorora kana kubvumidza zvabuda. Bata nhanho yega yega segedhi rehumbowo: kana maitiro asina kusangana, imbomira kuburitsa, vhara gaka, uye wobva wawedzera kushandiswa.
Label synthetic odhiyo uye chengetedza marekodhi ekuzvidavirira.
Label synthetic odhiyo uye chengetedza marekodhi ekuzvidavirira. Bata nhanho yega yega segedhi rehumbowo: kana maitiro asina kusangana, imbomira kuburitsa, vhara gaka, uye wobva wawedzera kushandiswa.