This paper presents early research results for a method for training neural networks to segment previously unseen continuous speech data into words, without the use of a lexicon or a speech recognition engine, or any other forms of supervision. The initial word segmentation is derived through a simple and naï ve method, and our method then leverages the time-invariant properties of the TDNN to ...

With deregulation and growth of the power industry, many power system elements such as generators, transmission lines, are driven to operate near their maximum capacity, especially those serving heavy load centres. Wide Area Controllers (WACs) using wide area or global signals can provide remote auxiliary control signals to local controllers such as automatic voltage regulators, power system st...

Because of containing several model waveforms and transmission speed of each model are various, the source signal of rub-impact acoustic emission (AE) will lead to waveform distortion in propagation process, and it is difficult to achieve exact source location by traditional time difference of arrival algorithm. A chaotic neural network technique was introduced to calculate the location of AE s...

The feasibility of distinguishing multiple type components of exo-atmospheric targets is demonstrated by applying the Time Delay Neural Network (TDNN) and the Adaptive Time-Delay Neural Network (ATNN). Exo-atmospheric targets are especially difficult to distinguish using currently available techniques because all target parts follow the same spatial trajectory. Thus, classification must be base...

This study introduces the classiication of musical instrument sounds by artiicial neural networks (ANN). The time varying spectral contents of sounds are estimated based on Short-time Fourier Transform (STFT) and are applied to ANN structures for classiication. Recognition results obtained from a multilayer perceptron (MLP), time delay neural network (TDNN) and a hybrid self organizing map radi...

Crying is the most noticeable behavior of infancy. Infant cry signals can be used to identify physical or psychological status of an infant. Recently, acoustic analysis of infant cry signal has shown promising results and it has been proven to be an excellent tool to investigate the pathological status of an infant. This paper proposes short-time Fourier transform (STFT) based time-frequency an...

This work addresses the cross-corpora generalization issue for low-resourced spoken language identification (LID) problem. We have conducted experiments in context of Indian LID and identified strikingly poor due to corpora-dependent non-lingual biases. Our contribution this is twofold. First, we propose domain diversification, which diversifies limited training data using different audio augme...

We proposed a model of Time Warping Invariant Neural Networks (TWINN) to handle the time warped continuous signals. Although TWINN is a simple modification of well known recurrent neural network, analysis has shown that TWINN completely removes time warping and is able to handle difficult classification problem. It is also shown that TWINN has certain advantages over the current available seque...

School of Computer Science Camegie Mellon University Pittsburgh, PA 15213, U.S.A. This paper describes a new structure of Neural Networks ("s) for speaker-independent and context-independent phoneme recognition. This structure is based on the integration of Time-Delay Neural Networks (TDNN) which have several TDNNs separated according to the duration of phonemes. As a result, the proposed struc...