Abstract--A set of Artificial Neural Network (ANN) based methods for the design of an effective system of speech recognition of numerals of Assamese language captured under varied ...
One of the difficult problems of acoustic modeling for Automatic Speech Recognition (ASR) is how to adequately model the wide variety of acoustic conditions which may be present i...
In an attempt to improve models of human perception, the recognition of phonemes in nonsense utterances was predicted with automatic speech recognition (ASR) in order to analyze i...
We focus in this paper on the named entity recognition task in spoken data. The proposed approach investigates the use of various contexts of the words to improve recognition. Exp...
Update of acoustic and language models is vital to maintain performance of automatic speech recognition (ASR) systems. To alleviate efforts for updating models, we propose a "...
Yuya Akita, Masato Mimura, Graham Neubig, Tatsuya ...
In this paper, we present a systems approach for channel modeling of an Automatic Speech Recognition (ASR) system. This can have implications in improving speech recognition compo...
Qun Feng Tan, Kartik Audhkhasi, Panayiotis G. Geor...
Abstract--An experimental research with a goal to automatically detect prominent words in Russian speech is presented in this paper. The proposed automatic prominent word detection...
Deploying an automatic speech recognition system with reasonable performance requires expensive and time-consuming in-domain transcription. Previous work demonstrated that non-pro...
High-level spoken document analysis is required in many applications seeking access to the semantic content of audio data, such as information retrieval, machine translation or au...
Julien Fayolle, Fabienne Moreau, Christian Raymond...
In this paper, we present a new method for video genre identification based on the linguistic content analysis. This approach relies on the analysis of the most frequent words in...