|
|
Domain Specific Data Crawling for Language Model Adaptation
Gregušová, Sabína ; Švec, Ján (referee) ; Karafiát, Martin (advisor)
The goal of this thesis is to implement a system for automatic language model adaptation for Phonexia ASR system. System expects input in the form of source that, which is analysed and appropriate terms for web search are chosen. Every web search results in a set of documents that undergo cleaning and filtering procedures. The resulting web corpora is mixed with Phonexia model and evaluated. In order to estimate the most optimal parameters, I conducted 3 sets of experiments for Hindi, Czech and Mandarin. The results of the experiments were very favourable and the implemented system managed to decrease perplexity and Word Error Rate in most cases.
|
|
|
Automatic Pronunciation Evaluation of Non-Native English Speakers
Gazdík, Peter ; Szőke, Igor (referee) ; Žmolíková, Kateřina (advisor)
Computer-Assisted Pronunciation Training (CAPT) is becoming more and more popular these days. However, the accuracy of existing CAPT systems is still quite low. Therefore, this diploma thesis focuses on improving existing methods for automatic pronunciation evaluation on the segmental level. The first part describes common techniques for this task. Afterwards, we proposed the system based on two approaches. Finally, performed experiments show significant improvement over the reference system.
|
|
|
The Best Possible Speech Recognizer on Your Own Data
Sýkora, Tomáš ; Veselý, Karel (referee) ; Szőke, Igor (advisor)
Denno-denne vzniká množstvo špičkových objavov v oblasti strojového učenia. Prispôsobením týchto sýstémov tak, aby čo najlepšie fungovali iba na obmedzenej podmnožine všeobecných dát, môžu byť dosiahnuté výrazné zlepšenia v prenosti. Prispôsobením automatického rozpoznávača reči na doménovo špecifické dáta je možné vytvoriť produkt dosahujúci omnoho lepšie výsledky ako rozpoznávač reči natrénovaný na všeobecných dátach. Táto práca prezentuje 17-percentné zlepšenie chybovosti prepísaných slov oproti automatickému rozpoznávaču reči ponúkaného službou Google Speech. Toto zlepšenie bolo dosiahnuté precíznou anotáciou a prípravou doménových dát a kombináciou špičkových techník a algoritmov v oblasti automatického rozpoznávania reči. Popísaný systém bol úspešne nasadený do výrobného prostredia transkripčnej spoločnosti Parrot, ktorej súčasťou som od jej začiatku. Nasadený systém výrazne zvýšil efektivitu zamestancov používajúcich výstup popísaného rozpoznávača.
|
|
|
Domain Specific Data Crawling for Language Model Adaptation
Gregušová, Sabína ; Švec, Ján (referee) ; Karafiát, Martin (advisor)
The goal of this thesis is to implement a system for automatic language model adaptation for Phonexia ASR system. System expects input in the form of source that, which is analysed and appropriate terms for web search are chosen. Every web search results in a set of documents that undergo cleaning and filtering procedures. The resulting web corpora is mixed with Phonexia model and evaluated. In order to estimate the most optimal parameters, I conducted 3 sets of experiments for Hindi, Czech and Mandarin. The results of the experiments were very favourable and the implemented system managed to decrease perplexity and Word Error Rate in most cases.
|
|
|
Automatic Pronunciation Evaluation of Non-Native English Speakers
Gazdík, Peter ; Szőke, Igor (referee) ; Žmolíková, Kateřina (advisor)
Computer-Assisted Pronunciation Training (CAPT) is becoming more and more popular these days. However, the accuracy of existing CAPT systems is still quite low. Therefore, this diploma thesis focuses on improving existing methods for automatic pronunciation evaluation on the segmental level. The first part describes common techniques for this task. Afterwards, we proposed the system based on two approaches. Finally, performed experiments show significant improvement over the reference system.
|
guest ::
