This paper presents a method of creating a new speaker’s voice database (VoiceFont) by which the voice of the donor speaker can be synthesized for mimicking in a text-to-speech system. A VoiceFont creation system, “VoiceFont Builder”, is developed to make the creation process easier and more effective than current systems. The voice feature extraction applied in the system is a simple but power...

The cascading appearance-based (CAB) feature extraction technique has established itself as the state of the art in extracting dynamic visual speech features for speech recognition. In this paper, we will focus on investigating the effectiveness of this technique for the related speaker verification application. By investigating the speaker verification ability of each stage of the cascade we w...

This paper presents a framework for evaluating phonetic feature extraction engines in a phone identification task. The case study involves HMM-based feature extraction engines for fricative and vocalic which are evaluated both at the feature level and also on how they perform when coupled with a knowledge-based phone identification model. An exact comparison model is defined and performance of ...

We propose in this paper a feature extraction method to extract brain wave features from electroencephalography (EEG) signal. The proposed feature extraction method is based on an assumption that EEG signal could be considered as stationary if the time window is sufficiently short. With this assumption, EEG signal has some similar properties to speech signal and hence a feature extraction metho...

We could show in the past that Hierarchical SpectroTemporal (HIST) features improve the performance of Automatic Recognition Systems (ARS) of speech in difficult environments when they are combined with conventional speech spectral features. The target here is to improve the noise robustness of the HIST features by investigating a channel distribution equalization in our feature hierarchy. Ther...

This paper describes the principle of MFCC feature extraction and the knowledge of human auditory masking effect in order to introduce a modified-MFCC feature extraction that can improve the robustness of speech recognition systems.

Automatic speech emotion recognition is a process of recognizing emotions in speech. This has wide applications in the area of phsycatrics help and in robotics’he human computer interaction the challenging area of research. Any effective HCI system has two sections Training and testing. The techniques used in the system are feature extraction and classification. This paper focuses on the brief ...

Speech is the most natural mode of communication. This work emphasizes on recognizing different emotions from speech signal. There are two major sections in this project namely feature extraction from speech signal and give this features as input to classifier to recognize emotions. Emotional states of speaker are considered as namely angry, happy, sad and neutral. The testing section classifie...

We investigated the speech recognition of a person with an articulation disorder resulting from the athetoid type of cerebral palsy. The articulation of the first speech tends to become unstable due to strain on speech-related muscles, and that causes degradation of speech recognition. In this paper, we introduce a robust feature extraction method based on PCA (Principal Component Analysis) and...