GUIDE IA Audio

Audio yuñ dugal ak jàngat ci representation

Embeddings audio yi dañuy soppi son bi mu nekk vecteur numérique yu kompact yuy jàpp luñuy tekki, suko defee masin yi mëna méngale, seetee, ak xaaj audio yi ci anam wi nit ñi di xàmmee baat wala way buñ miin.

Résumé

Embeddings audio yi dañuy soppi son bi mu nekk vecteur numérique yu kompact yuy jàpp luñuy tekki, suko defee masin yi mëna méngale, seetee, ak xaaj audio yi ci anam wi nit ñi di xàmmee baat wala way buñ miin. Mooy motër bi nëbbu ci ginaaw xàmmee kàddu yi, xelal music ak seetlu son.

Audio Embeddings ak Representation Learning mingi toog ci biir audio-IA buy soppi kàddu, music, ak son ngir jokkoo, yombal jëfandikoo gi, ak defar media.

Plongeur bu xóot

Embedding audio mooy limu nimero yu am guddaay bu takku (vecteur) buy màndargaal benn clip son ci anam wuy boole son yu nuróo ci espace math. Ñaari enregistrement yu benn baat, wala ñaari way ci benn genre, dañuy mujjee nekk ci wetu seen biir doonte seeni forme onde yu wuute lool. Model yi dañu jàng embeddings yooyu ci tàggat ci audio yu bari, lu bari ci ñoom duñu am etiketu nit. Sistem yiy saytu seen bopp yu melni Wav2Vec 2.0, HuBERT, ak CLAP dañuy jàng ci seetlu ay pàcci audio yu maske wala yu wuute. Buñu ko tàggatee, mën nañu jëfandikoowaat benn embeddings bi ci liggéey yu bari ci suuf (ID kàddukat, yëg-yëg, etiketu music) ak done yu néew yuñ yokk, moo tax jàng representation am solo lool.

Gis-gis xarala

Audio bu ñor ay milioŋ ciy misaal la ci simili bu nekk, kon model yi dañu koy njëkka soppi def ko spectrogram wala filtre yuñ jàng, ba noppi ñu jàll ko ci transformatër wala reso convolutionnel. Mébet yi ñuy saytu seen bopp ñooy gëna am solo: Wav2Vec 2.0 dafay maske span audio yi ba noppi jàng tànnee unité quantifié bu dëggu ci distractors yi, ci noonu la model yu wuute yu melni CLAP di xëcc ñaari audio-tekst yu méngoo ak push mismatches yi. Lépp soo ko boolee mu nekk vecteur bu dëgër, lu bari ay téemeeri wala junni dimension, muy kode fonetik, waxkat, ak structure akustik.

Jàngale ay mbir yuy boole ay audio ak ay représentation

Ngir gëna am xam-xam bu xóot, jàppal Embeddings Audio ak Representation Learning ni xeetu liggéey, du benn man-man. Mandargal njariñ yi nga bëgg, leeral li nga xalaat, ba noppi tàqale li sistem bi mëna def ci anam wu wóor ak liy laaj ba leegi àtteb kàngam.

Ci jëf, ekip yu am doole yiy jëfandikoo Audio Embeddings ak Representation Learning dañuy jàppee kalite, latency, ak nangu ni cër yu am solo ci pexem jëfandikoo gi. Dañuy bind kritër yu leer ngir am ndam, natt leen ci done yu dëggu ak def liggéey, ba noppi ñu baamtu ci anamu ñàkka mëna seetlu, du ci benn yoon benchmark wins. Mooy barab bi xam-xam theorie bi di soppiku nekk kàttan buy yàgg ci produit yi, ci politik yi ak ci liggéey yi.

Dafay gëna yombal jëfandikoo gi jaaraleko ci transkripsioŋ, nettali ak interfaasu baat. Ci jamano jooju, risku jëfandikoo Baat bu baaxul ak niru ak nit dafay gëna yokk sudee nanguwul. Xeetu jëf bi gëna dëgër mooy boole gaawaayu jàngat ak disipline nguur: doxal pilote, jàpp firnde, siiwal dogal yi, ak wéy di yeesal kaaraange gi ci anam wi ñuy doxalee, li jëfandikukat bi di xaar, ak sàrti sàrt yi di jëm kanam.

njeextalu pexe

Dafay gëna yombal jëfandikoo gi jaaraleko ci transkripsioŋ, nettali ak interfaasu baat.

Dafay gëna yombal jëfandikoo gi jaaraleko ci transkripsioŋ, nettali ak interfaasu baat. Ci jëfandikoo yu am kalite bu kawe, loolu dañu koy tekki ci sàrti liggéey yuñ mëna natt, ay peggu boroom, ak ay xew-xewu xoolaat yu bari suko defee ekip yi mëna yokk wóolu seen bopp ci barabu yokk lu jaxasoo.

Ekipu mejaa yi mën nañu yónnee audio bu leer ci anam wu gëna gaaw te seen xaalis gëna néew.

Ekipu mejaa yi mën nañu yónnee audio bu leer ci anam wu gëna gaaw te seen xaalis gëna néew. Ci jëfandikoo yu am kalite bu kawe, loolu dañu koy tekki ci sàrti liggéey yuñ mëna natt, ay peggu boroom, ak ay xew-xewu xoolaat yu bari suko defee ekip yi mëna yokk wóolu seen bopp ci barabu yokk lu jaxasoo.

Sistem yiy jàkkarloo ak kiliyaan bi mën nañu def waxtaan ci anam wu gëna yaatu.

Sistem yiy jàkkarloo ak kiliyaan bi mën nañu def waxtaan ci anam wu gëna yaatu. Ci jëfandikoo yu am kalite bu kawe, loolu dañu koy tekki ci sàrti liggéey yuñ mëna natt, ay peggu boroom, ak ay xew-xewu xoolaat yu bari suko defee ekip yi mëna yokk wóolu seen bopp ci barabu yokk lu jaxasoo.

Ëlëgu ëmbeefi audio ak jàng representation

Xaarandil ni embeddings audio yi dina ñu gëna bari ay anam yu wuute, boole ci bind ak wideo suko defee benn model mëna dégg son, kàddu yi ak nataal yi ci benn seen. Barabu làkk audio yuñ boole lu melni CLAP dañuy may seetug son ci làkk wiñ nàmp ('gis xaj buy waay ci wetu dem bi ak dikk bi'). Ay xeetu embedding yu gina ndaw, ci aparey yi dinañu dooleel ay man-mani baat yu kenn xamul ci telefon yi ak ay earbuds, ci noonu la taggat bu gina riis bi ñuy saytu boppam di wey di dagg limu done yiñ soxla ci lakk yu bees yi ak xew xew akustik yu nééw yi.

Doxal ci àdduna dëgg

Aplikaasioŋu music yu melni Spotify dañuy jëfandikoo ay embedding ngir digal way yu 'nuru' ba ci genre yépp ak ngir dooleel emprent audio.

Aplikaasioŋ yu nuroo ak yu Shazam dañuy méngale enregistrement bu bari bruit ak track ci méngale emprent baraam yiñ ci samp, du audio bu ñor.

Oparlër yu xarañ yi ak telefon yi dañuy jëfandikoo ay oparlër yuñ samp (empre baat) ngir xàmmee waa kër gi ak personaalise tontu yi.

Call center yi ak jumtukaayi ndaje yi dañuy jëfandikoo ay embeddings ngir diarization waxinkat yi, ngir xàmmee kan moo wax ci enregistrement bi.

Modèlu jëfandikoo

Audio yuñ dugal ak jàngat ci jëf

Aplikaasioŋu music yu melni Spotify dañuy jëfandikoo ay embedding ngir digal way yu 'nuru' ba ci genre yépp ak ngir dooleel emprent audio.

Ekip yi dañuy faral di am njariñ yu gëna baax suñu tëralee ay threshold yu baax ci kanam, tëye yoonu escalation nit ngir jafe-jafe yi, ba noppi topp benefiis yi ak njëgu njuumte yi ci diir bi.

Audio yuñ dugal ak jàngat ci jëf

Aplikaasioŋ yu nuroo ak yu Shazam dañuy méngale enregistrement bu bari bruit ak track ci méngale emprent baraam yiñ ci samp, du audio bu ñor.

Ekip yi dañuy faral di am njariñ yu gëna baax suñu tëralee ay threshold yu baax ci kanam, tëye yoonu escalation nit ngir jafe-jafe yi, ba noppi topp benefiis yi ak njëgu njuumte yi ci diir bi.

Audio yuñ dugal ak jàngat ci jëf

Oparlër yu xarañ yi ak telefon yi dañuy jëfandikoo ay oparlër yuñ samp (empre baat) ngir xàmmee waa kër gi ak personaalise tontu yi.

Ekip yi dañuy faral di am njariñ yu gëna baax suñu tëralee ay threshold yu baax ci kanam, tëye yoonu escalation nit ngir jafe-jafe yi, ba noppi topp benefiis yi ak njëgu njuumte yi ci diir bi.

Audio yuñ dugal ak jàngat ci jëf

Call center yi ak jumtukaayi ndaje yi dañuy jëfandikoo ay embeddings ngir diarization waxinkat yi, ngir xàmmee kan moo wax ci enregistrement bi.

Ekip yi dañuy faral di am njariñ yu gëna baax suñu tëralee ay threshold yu baax ci kanam, tëye yoonu escalation nit ngir jafe-jafe yi, ba noppi topp benefiis yi ak njëgu njuumte yi ci diir bi.

Risk yi ak balustrade yi

!

Jëfandikoo baat ci anam wu jaarul yoon ak niru ak nit dafay gëna yokk sudee nanguwul.

!

Jaar-jaar mën na wàññeeku ci aksan yi, dialect yi wala barab yu bari xumbaay.

!

Audio synthetik mën nañu ko jaawale ak wax ju dëggu sudee amul etiket bu leer.

Roadmap ngir samp gi

1

Wutal ndigal bu leer ngir jàpp baat bi, klone ko ak jëfandikoowaat ko.

Jàppaleel lii ni buntu firnde: sudee mattul kritër yi, dakkal génne gi, tëj bërëb bi, suko defee nga yaatal jëfandikoo gi.

2

Saytu kalite ci kàddukat yu bari ak anam yu bari ci ginaaw.

Jàppaleel lii ni buntu firnde: sudee mattul kritër yi, dakkal génne gi, tëj bërëb bi, suko defee nga yaatal jëfandikoo gi.

3

Mandargal kañ la nit wara xoolaat wala nangu ay génne.

Jàppaleel lii ni buntu firnde: sudee mattul kritër yi, dakkal génne gi, tëj bërëb bi, suko defee nga yaatal jëfandikoo gi.

4

Etiketu audio synthetik te nga denc dokimaa ci fimu bawoo ngir mëna lim.

Jàppaleel lii ni buntu firnde: sudee mattul kritër yi, dakkal génne gi, tëj bërëb bi, suko defee nga yaatal jëfandikoo gi.

Weyal di banneexu

Check your understanding

Test yourself: take the Audio Embeddings and Representation Learning quiz

Start quiz