Voice and emotional expression transformation based on statistics of vowel parameters in an emotional speech database
نویسندگان
چکیده
We propose a simple method for modifying emotional speech sounds. The method aims at real-time implementation of an emotional expression transformation system based on STRAIGHT. We developed a mapping function of spectra, fundamental frequencies (F0), and vowel durations from the statistical analysis of 1500 expressive speech sounds in an emotional speech database. The spectral mapping parameters are initially extracted at the centers of vowels and interpolated with bilinear functions. The spectral frequency warping functions are manually designed. The F0 and duration mapping functions simply transform the average values in log frequency and linear time scales. We demonstrate that the spectral distortion is small enough when ‘Neutral’ speech sounds are transformed to expressive speech sounds (i.e. ‘Bright’, ‘Excited’, ‘Angry’, and ‘Raging’ speech sounds).
منابع مشابه
Comparing the Voice Handicap Index Scores in Groups with Structural and Functional Voice Disorders
Objective: The effects of voice disorders vary from person to person. Occupation, work environment, life, and family reaction are variables that affect one’s perception of his/her own as an impaired voice. Voice Handicap Index (VHI) has not yet been used to compare the degree of voice disorders. Assuming that the quality of life may be different under a variety of voice disorders and that diffe...
متن کاملSpeech Emotion Recognition Based on Power Normalized Cepstral Coefficients in Noisy Conditions
Automatic recognition of speech emotional states in noisy conditions has become an important research topic in the emotional speech recognition area, in recent years. This paper considers the recognition of emotional states via speech in real environments. For this task, we employ the power normalized cepstral coefficients (PNCC) in a speech emotion recognition system. We investigate its perfor...
متن کاملRecognizing the Emotional State Changes in Human Utterance by a Learning Statistical Method based on Gaussian Mixture Model
Speech is one of the most opulent and instant methods to express emotional characteristics of human beings, which conveys the cognitive and semantic concepts among humans. In this study, a statistical-based method for emotional recognition of speech signals is proposed, and a learning approach is introduced, which is based on the statistical model to classify internal feelings of the utterance....
متن کاملImmediate effects of vocal warm-up exercises on elementary teachers' voice
Introduction: Teachers are a large group of professional voice users who are exposed to many voice problems. Vocal warm-up exercises (VWUE) can prepare the muscles involved in vocalization before teaching and can reduce voice damage in teachers. However, limited studies have examined the effects of VWUE on teachers' voices. Therefore, the present study was conducted to investigate the immediate...
متن کاملStudy on Unit-Selection and Statistical Parametric Speech Synthesis Techniques
One of the interesting topics on multimedia domain is concerned with empowering computer in order to speech production. Speech synthesis is granting human abilities to the computer for speech production. Data-based approach and process-based approach are the two main approaches on speech synthesis. Each approach has its varied challenges. Unit-selection speech synthesis and statistical parametr...
متن کامل