Mgbakwunye ọdịyo na mmụta nnọchite anya
Ihe ntinye ọnụnụ na-atụgharị ụda ka ọ bụrụ vector kọmpat nke na-ewepụta ihe ọ pụtara, ya mere igwe nwere ike iji tụnyere, chọọ ma hazie ọdịyo ka mmadụ si amata olu ma ọ bụ egwu ama ama.
Nchịkọta
They are the hidden engine behind speech recognition, music recommendation, and sound search.
Ime miri emi
Ntinye ọdịyo bụ ndepụta ọnụọgụ ogologo (vector) nke na-anọchi anya obere ụda n'ụzọ na-etinye ụda yiri ya nso na oghere mgbakọ na mwepụ. Edekọ abụọ nke otu okwu, ma ọ bụ abụ abụọ n'otu ụdị, na-abịaru ibe ha nso ọbụlagodi ma ọ bụrụ na ụdị ebili mmiri ha dị iche iche. Ụdị na-amụta ihe mgbakwụnye ndị a site n'ịzụ ọzụzụ n'ọtụtụ ọdịyo, na-enweghị akara mmadụ. Sistemu na-ahụ maka onwe ya dị ka Wav2Vec 2.0, HuBERT na CLAP na-amụta site n'ibu amụma nchikota nke ihe mkpuchi ma ọ bụ iche. Ozugbo a zụrụ azụ, enwere ike ijikwa otu ntinye ahụ maka ọtụtụ ọrụ dị n'okpuru ala (NJ ọkà okwu, mmetụta uche, mkpado egwu) yana obere data agbakwunyere aha, nke mere na mmụta nnọchite anya bara uru.
Nghọta nka nka
Audio ọdịyo bụ ọtụtụ nde nlele kwa nkeji, yabụ ụdị na-ebu ụzọ tụgharịa ya ka ọ bụrụ spectrograms ma ọ bụ ihe nzacha mmụta, wee nyefee ya na transformers ma ọ bụ netwọkụ mgbanwe. Ebumnobi na-elekọta onwe ya bụ isi: Wav2Vec 2.0 na-ekpuchi ụda olu wee mụta ịhọpụta otu nkeji ziri ezi site na ndị na-adọpụ uche, ebe ụdị dị iche iche dị ka CLAP na-esetịpụ ụzọ abụọ ederede ọdịyo na-adakọ ọnụ ma na-ekewapụ adịghị mma. Ihe si na ya pụta bụ vector siri ike, na-abụkarị akụkụ narị ole na ole ruo otu puku, nke na-etinye koodu ụda olu, ọkà okwu, na nhazi ụda.
Mmetụta atụmatụ
Nweta na iru
Ọ na-eme ka nnweta ya dịkwuo mma site na ndegharị, ịkọ akụkọ, na ntụgharị olu.
Ọnụ ego na mmefu ego
Ndị otu mgbasa ozi nwere ike ibubata ọdịyo a na-egbu maramara ngwa ngwa site na iji obere mmefu ego.
Ọsọ na ọnụ ọgụgụ
Sistemụ na-eche ihu ndị ahịa nwere ike hazie mkparịta ụka n'ọtụtụ buru ibu.
Ọdịnihu nke ntinye ọdịyo na mmụta nnọchite anya
Na-atụ anya na ntinye ọdịyo ga-aghọwanye multimodal, jikọtara ya na ederede na vidiyo ka otu ụdị ghọta ụda, okwu, na ihe nkiri ọnụ. Oghere asụsụ ọnụ ọnụ ọnụ dị ka CLAP na-eme ka ịchọọ ụda asụsụ okike ('chọta nkịta na-agbọ n'akụkụ okporo ụzọ'). Ụdị ntinye dị obere, nke dị na ngwaọrụ ga-eme ka njirimara olu na-anọghị n'ịntanetị na ekwentị na ntị ntị, ebe ọzụzụ nlekọta onwe onye ka ukwuu na-anọgide na-ebelata ọnụọgụ data akara achọrọ maka asụsụ ọhụrụ yana mmemme egwu na-adịghị ahụkebe.
Mmejuputa n'ezie n'ụwa
Ngwa egwu dị ka Spotify na-eji ntinye iji kwado egwu ndị 'na-ada otu' ọbụlagodi n'ụdị dị iche iche na iji mee ka mkpisiaka ọdịyo dị ike.
Ngwa ụdị Shazam dabara na ndekọ mkpọtụ na egwu site n'ịtụnyere akara mkpịsị aka karịa ụda nkịtị.
Ndị ọkà okwu smart na ekwentị na-eji ntinye okwu (mpịakọta olu) agwa ndị ezinaụlọ iche wee hazie nzaghachi.
Ebe oku na ngwa nzuko na-eji ntinye maka ịkpọ okwu okwu, na-achọpụta onye kwuru mgbe nọ na ndekọ.
Ihe ize ndụ & okporo ụzọ nche
Iji olu eme ihe na ihe egwu mpụta ga-abawanye mgbe nkwenye na-efu.
Izi ezi nwere ike ịdaba n'ofe ụda olu, olumba ma ọ bụ gburugburu mkpọtụ.
Enwere ike imehie ọdịyo sịntetik dị ka ezigbo okwu na-enweghị akara doro anya.
Map mmejuputa
Nweta nkwenye doro anya maka ijide olu, imechi, na ijigharị.
Nwale ogo n'ofe ndị na-ekwu okwu dị iche iche yana ọnọdụ ndabere.
Kọwaa mgbe mmadụ ga-enyocha ma ọ bụ kwado nsonye.
Deba aha ọdịyo sịntetik ma debe ndekọ ihe ndekọ maka ịza ajụjụ.
Nọgide na-eme nchọpụta
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Ntuziaka na-esote
Ntinye ihe nnọchi anya Matryoshka
Ajụjụ a na-ajụkarị
What is Audio Embeddings and Representation Learning?
Ihe ntinye ọnụnụ na-atụgharị ụda ka ọ bụrụ vector kọmpat nke na-ewepụta ihe ọ pụtara, ya mere igwe nwere ike iji tụnyere, chọọ ma hazie ọdịyo ka mmadụ si amata olu ma ọ bụ egwu ama ama. Ha bụ injin zoro ezo n'azụ njirimara okwu, nkwanye egwu, na nchọ ụda.
Gịnị bụ ntinye ọdịyo?
Ihe ntinye bụ vector ọnụọgụgụ nke na-edobe obere vidiyo na-ada ụda na nso nso na oghere mgbakọ na mwepụ, na-esetịpụ ihe ọ pụtara kama ịbụ naanị ihe atụ.
Kedu ihe kpatara mmụta nke onwe ya ji dị mkpa maka ntinye ọdịyo?
Ụzọ a na-ahụ maka onwe ya dị ka Wav2Vec 2.0 na HuBERT na-amụta site na nnukwu ụda nke enweghị akara, ya mere, ọrụ ndị dị n'okpuru ala chọrọ data enweghị aha.
Kedu ka Wav2Vec 2.0 si amụta n'oge ọzụzụ ọzụzụ?
Wav2Vec 2.0 na-eji ebumnobi kpuchiri ekpuchi, nke dị iche: ọ na-ezochi ogologo ọdịyo wee mụta ịmata akụkụ latent ziri ezi yana ihe ndọpụ uche.
Kedu ihe ihe nlereanya dị ka CLAP na-ahazi n'ime oghere nkekọrịta?
CLAP (Asụsụ Contrastive-Audio Pretraining) na-amụta oghere nkwonkwo ebe obere vidiyo na nkọwa ederede ha na-adakọ ọnụ, na-eme ka ọchụchọ ụda dabere na ederede.
Tupu ịnye ọdịyo na netwọkụ akwara ozi, kedu mgbanwe a na-ejikarị eme ihe?
Ụdị ebili mmiri raw nwere ọtụtụ nde nlele, yabụ a na-atụgharịkarị ụda ka ọ bụrụ spectrograms ma ọ bụ gafere site na nzacha ihu-azụ amụtara n'ihu netwọkụ bụ isi.