Transformation of formants for voice conversion using artificial neural networks

نویسندگان

  • M. Narendranath
  • Hema A. Murthy
  • S. Rajendran
  • Bayya Yegnanarayana
چکیده

In this paper we propose a scheme for developing a voice conversion system that converts the speech signal uttered by a source speaker to a speech signal having the voice characteristics of the target speaker. In particular, we address the issue of transformation of the vocal tract system features from one speaker to another. Formants are used to represent the vocal tract system features and a formant vocoder is used for synthesis. The scheme consists of a formant analysis phase, followed by a learning phase in which the implicit formant transformation is captured by a neural network. The transformed formants together with the pitch contour modified to suit the average pitch of the target speaker are used to synthesize speech with the desired vocal tract system characteristics.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

A Review of Epidemic Forecasting Using Artificial Neural Networks

Background and aims: Since accurate forecasts help inform decisions for preventive health-careintervention and epidemic control, this goal can only be achieved by making use of appropriatetechniques and methodologies. As much as forecast precision is important, methods and modelselection procedures are critical to forecast precision. This study aimed at providing an overview o...

متن کامل

Voice Disorders Identification Using Hybrid Approach: Wavelet Analysis and Multilayer Neural Networks

This paper presents a new strategy of identification and classification of pathological voices using the hybrid method based on wavelet transform and neural networks. After speech acquisition from a patient, the speech signal is analysed in order to extract the acoustic parameters such as the pitch, the formants, Jitter, and shimmer. Obtained results will be compared to those normal and standar...

متن کامل

Transformation of spectral envelope for voice conversion based on radial basis function networks

This paper presents a novel algorithm that modifies the speech uttered by a source speaker to sound as if produced by a target speaker. In particular, we address the issue of transformation of the vocal tract characteristics from one speaker to another. The approach is based on estimating spectral envelopes using radial basis function (RBF) networks, which is one of the well-known models of art...

متن کامل

Application of Linear Regression and Artificial NeuralNetwork for Broiler Chicken Growth Performance Prediction

This study was conducted to investigate the prediction of growth performance using linear regression and artificial neural network (ANN) in broiler chicken. Artificial neural networks (ANNs) are powerful tools for modeling systems in a wide range of applications. The ANN model with a back propagation algorithm successfully learned the relationship between the inputs of metabolizable energy (kca...

متن کامل

Real-time voice conversion using artificial neural networks with rectified linear units

This paper presents an approach to parametric voice conversion that can be used in real-time entertainment applications. The approach is based on spectral mapping using an artificial neural network (ANN) with rectified linear units (ReLU). To overcome the oversmoothing problem a special network configuration is proposed that utilizes temporal states of the speaker. The speech is represented usi...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:
  • Speech Communication

دوره 16  شماره 

صفحات  -

تاریخ انتشار 1995