Modeling Speaker Personality Using Voice
نویسندگان
چکیده
In this paper, we validate the application of an established personality assessment and modeling paradigm to speech input, and extend earlier work towards text independent speech input. We show that human labelers can consistently label acted speech data generated across multiple recording sessions, and investigate further which of the 5 scales in the NEO-FFI scheme can be assessed from speech, and how a manipulation of one scale influences the perception of another. Finally, we present a clustering of human labels of perceived personality traits, which will be useful in future experiments on automatic classification and generation of personality traits from speech.
منابع مشابه
Modeling speaking rate for voice fonts
Voice fonts are created and stored for a speaker, to be used to synthesize speech in the speaker’s voice. The most important descriptors of voice fonts are spectral envelope for acoustic units and prosodic features such as fundamental frequency and average speaking rate. In this paper, we present a new approach to model the speaking rate so that it can be easily incorporated in voice fonts and ...
متن کاملEigen-Voice Based Anchor Modeling System for Speaker Identification Using MLLR Super-Vector
In this paper, we propose an anchor modeling scheme where instead of conventional “anchor” speakers, we use eigenvectors that span the Eigen-voice space. The computational advantage of conventional Anchor-modeling based speaker identification system comes from representing all speakers in a space spanned by a small number of anchor speakers instead of having separate speaker models. The convent...
متن کاملطراحی یک روش آموزش ناموازی جدید برای تبدیل گفتار با عملکردی بهتر از آموزش موازی
Introduction: The art of voice mimicking by computers, has with the computer have been one of the most challenging topics of speech processing in recent years. The system of voice conversion has two sides. In one side, the speaker is the source that his or her voice has been changed for mimicking the target speaker’s voice (which is on the other side). Two methods of p...
متن کاملModeling a Noisy-channel for Voice Conversion Using Articulatory Features
In this paper, we propose modeling a noisy-channel for the task of voice conversion (VC). We have used the artificial neural networks (ANN) to capture speaker-specific characteristics of a target speaker which avoid the need for any training utterance from a source speaker. We use articulatory features (AFs) as a canonical form or speaker-independent representation of a speech signal. Our studi...
متن کاملImproved average-voice-based speech synthesis using gender-mixed modeling and a parameter generation algorithm considering GV
For constructing a speech synthesis system which can achieve diverse voices, we have been developing a speaker independent approach of HMM-based speech synthesis in which statistical average voice models are adapted to a target speaker using a small amount of speech data. In this paper, we incorporate a high-quality speech vocoding method STRAIGHT and a parameter generation algorithm with globa...
متن کامل