Abstract. The main goal of this work is the adaptation of a broadcast news transcription system to a new domain, namely, the Portuguese Parliament plenary meetings. This paper describes the different domain adaptation steps that lowered our baseline absolute word error rate from 20.1 % to 16.1%. These steps include the vocabulary selection, in order to include specific domain terms, language model adaptation, by interpolation of several different models, and acoustic model adaptation, using an unsupervised confidence based approach
This paper investigates the effectiveness of online temporal language model adaptation when applied ...
Modern speech recognition systems exhibits rapid performance degradation under domain shift. This is...
Automatic speech recognition models are often adapted to improve their accuracy in a new domain. A p...
Abstract. Up-to-date language modeling is recognized to be a critical aspect of maintaining the leve...
This thesis explores the idea of talk-level domain adaptation for automatic speech recognition (ASR)...
The daily and real-time transcription of Broadcast News (BN) is a challenging task both in acoustic ...
This paper reports on experiments of porting the ITC-irst Italian broadcast news (BN) recognition sy...
In this work we investigate methods to extend the lexicon of a broadcast news (BN) speech recognitio...
This paper reports on experiments of porting the ITC-irst Italian broadcast news recognition system ...
This paper investigates the problem of updating over time the statistical language model (LM) of an ...
The paper describes recent progress in the development the Slovak language models for transcription ...
The use of the PC and Internet for placing telephone calls will present new opportunities to capture...
Machine translation research has progressed in recent years thanks to statistical machine learning m...
This study investigates the possibility of using statistical machine translation to create domain-sp...
This paper reports on experiments of porting the ITC-irst Italian broadcast news recognition system ...
This paper investigates the effectiveness of online temporal language model adaptation when applied ...
Modern speech recognition systems exhibits rapid performance degradation under domain shift. This is...
Automatic speech recognition models are often adapted to improve their accuracy in a new domain. A p...
Abstract. Up-to-date language modeling is recognized to be a critical aspect of maintaining the leve...
This thesis explores the idea of talk-level domain adaptation for automatic speech recognition (ASR)...
The daily and real-time transcription of Broadcast News (BN) is a challenging task both in acoustic ...
This paper reports on experiments of porting the ITC-irst Italian broadcast news (BN) recognition sy...
In this work we investigate methods to extend the lexicon of a broadcast news (BN) speech recognitio...
This paper reports on experiments of porting the ITC-irst Italian broadcast news recognition system ...
This paper investigates the problem of updating over time the statistical language model (LM) of an ...
The paper describes recent progress in the development the Slovak language models for transcription ...
The use of the PC and Internet for placing telephone calls will present new opportunities to capture...
Machine translation research has progressed in recent years thanks to statistical machine learning m...
This study investigates the possibility of using statistical machine translation to create domain-sp...
This paper reports on experiments of porting the ITC-irst Italian broadcast news recognition system ...
This paper investigates the effectiveness of online temporal language model adaptation when applied ...
Modern speech recognition systems exhibits rapid performance degradation under domain shift. This is...
Automatic speech recognition models are often adapted to improve their accuracy in a new domain. A p...