Speech Bandwidth Extension Method Research Articles

Telephony Speech Enhancement Using Threshold Estimation Based Data Hiding

Public telephone system transmit speech across a limited frequency range, about 300–3400 Hz, called narrowband (NB) which results in a significant reduction of quality and intelligibility of speech. This paper proposes a fully backward compatible novel method for bandwidth extension of NB speech. The method uses threshold estimation based technique to provide a perceptually better wideband speech signal. The CELP parameters are extracted from the high frequency components of speech signal existing above NB, which are then spread by using spreading sequences, and are embedded in the NB speech signal using threshold estimation based data hiding technique. The embedded information is extracted at the receiving end to reconstruct the wideband speech signal. Theoretical and simulation analyses show that the proposed method is robust to quantization and channel noises. The log spectral distortion test clearly show that the reconstructed wideband signal gives a much better performance in terms of speech quality when compared to the conventional speech bandwidth extension methods employing data hiding..

Adaptive Data Hiding Based Telephony Speech Enhancement

Public telephone systems transmit speech across a limited frequency range, about 300–3400 Hz, called narrowband (NB) which results in a significant reduction of quality and intelligibility of speech. This paper proposes a fully backward compatible novel method for bandwidth extension of NB speech. The method uses adaptive data hiding technique to provide a perceptually better wideband speech signal. The spectral envelope parameters are extracted from the high frequency components of speech signal existing above NB, which are then spread by using spreading sequences, and are embedded in the NB speech signal using adaptive data hiding technique. The embedded information is extracted at the receiving end to reconstruct the wideband speech signal. Theoretical and simulation analyses show that the proposed method is robust to quantization and channel noises. The log spectral distortion test clearly show that the reconstructed wideband signal gives a much better performance in terms of speech quality when compared to the conventional speech bandwidth extension methods employing data hiding.

Transform-Domain Speech Bandwidth Extension

The limited speech bandwidth used in narrowband telephone systems degrades both the quality and the intelligibility of speech. This paper proposes a new transform-domain speech bandwidth extension method. The method uses discrete wavelet transform–fast Fourier transform-based data hiding technique to provide a better quality wideband speech signal. The code-excited linear prediction parameters of the missing speech are hidden within the narrowband speech signal. The hidden information is recovered at the receiving end to produce a wideband speech signal. Theoretical and simulation analyses show that the proposed method is robust to quantization and channel noises. Obtained results confirm the excellent reconstructed wideband speech quality of the proposed method over traditional methods.

Speech Bandwidth Extension Aided by Magnitude Spectrum Data Hiding

Public telephone systems transmit speech across a limited frequency range, about 300–3400 Hz, called narrowband (NB) which results in a significant reduction of quality and intelligibility of speech. This paper proposes a fully backward compatible novel method for bandwidth extension of NB speech. The method uses magnitude spectrum data hiding technique to provide a perceptually better wideband speech signal. The spectral envelope parameters are extracted from the down-sampled frequency shifted version of the high-frequency components of speech signal existing above NB, which are then encoded and spread by using spreading sequences, and are embedded in the low-amplitude high-frequency regions of the magnitude spectrum of NB speech signal. The embedded information is extracted at the receiving end to reconstruct the wideband speech signal. Theoretical and simulation analyses show that the proposed method is robust to quantization and channel noises. The comparison category rating listening and log spectral distortion tests clearly show that the reconstructed wideband signal gives a much better performance in terms of speech quality when compared to the conventional speech bandwidth extension methods employing data hiding.

Bandwidth extension of telephone speech using magnitude spectrum data hiding

Public telephone systems transmit speech across a limited frequency range, about 300---3400 Hz, called narrowband (NB) which results in a significant reduction of quality and intelligibility of speech. This paper proposes a fully backward compatible novel method for bandwidth extension of NB speech. The method uses magnitude spectrum data hiding technique to provide a perceptually better wideband speech signal. Code excited linear prediction parameters are extracted from the down sampled frequency shifted version of the high frequency components of speech signal existing above NB, which are spread by using pseudo-noise codes, and are embedded in the low amplitude high-frequency regions of the magnitude spectrum of NB speech signal. The embedded information is extracted at the receiving end to reconstruct the wideband speech signal. Theoretical and simulation analyses show that the proposed method is robust to quantization and channel noises. The comparison category rating listening and log spectral distortion tests clearly show that the reconstructed wideband signal gives a much better performance in terms of speech quality when compared to some of the existing speech bandwidth extension methods employing data hiding.

Speech Bandwidth Extension Using Recurrent Temporal Restricted Boltzmann Machines

In this paper, we present a new speech bandwidth extension method (BWE) using recurrent temporal restricted Boltzmann machine (RTRBM). The conventional Gaussian mixture model (GMM)-based and deep neural networks (DNNs)-based BWE methods perform stably and effectively. However, the mapping function of GMM-based methods is a piecewise linear transformation, which is insufficient to model the complex nonlinear mapping relationship between the spectral envelope features of low frequency (LF) and high frequency (HF). In the conventional DNNs methods, temporal correlations across speech frames are ignored, resulting in spectral detail loss of the reconstructed speech by BWE. To counter these issues, a multilayer DNN which is composed of two RTRBMs and a feedforward neural network (NN) is employed to obtain time information and model deep nonlinear relationships between the spectral envelope features of LF and HF. The proposed method takes advantage of the strong ability of RTRBM in discovering the temporal correlation in the high-order space and modeling deep nonlinear relationships between input and output. Both the objective and subjective evaluations indicate that our proposed method outperforms the conventional GMM-based methods and other NN-based methods.

An audio watermark-based speech bandwidth extension method

Abstract A novel speech bandwidth extension method based on audio watermark is presented in this paper. The time-domain and frequency-domain envelope parameters are extracted from the high-frequency components of speech signal, and then these parameters are embedded in the corresponding narrowband speech bit stream by the modified least significant bit watermark method which uses perception property. At the decoder, the wideband speech is reproduced with the reconstruction of high-frequency components based on the parameters extracted from bit stream of the narrowband speech. The proposed method can decrease poor auditory effect caused by large local distortion. The simulation results show that the synthesized wideband speech has low spectral distortion and its speech perception quality is greatly improved.

Evaluation of an Artificial Speech Bandwidth Extension Method in Three Languages

Quality and intelligibility of narrowband telephone speech can be improved by artificial bandwidth extension (ABE), which extends the speech bandwidth using only information available in the narrowband speech signal. This paper reports a three-language evaluation of an ABE method that has recently been launched in several of Nokia's mobile telephone models. The method extends the speech bandwidth to frequencies above the telephone band by first utilizing spectral folding and then modifying the magnitude spectrum of the extension band with spline curves. The performance of the method was evaluated by formal listening tests in American English, Russian, and Mandarin Chinese. The results of the listening tests indicate that ABE processing improved the subjective quality of coded narrowband speech in all these languages. Differences between bandwidth-extended American English test sentences and their original wideband counterparts were also evaluated using both an objective distance measure that simulates the characteristics of human hearing and a conventional spectral distortion measure. The average objective error was calculated for different categories of speech sounds. The error was found to be smallest in nasals and semivowels and largest in fricative sounds.

Low-complexity feature-mapped speech bandwidth extension

Today's telecommunications systems use a limited audio signal bandwidth. A typical bandwidth is 0.3-3.4 kHz, but recently it has been suggested that mobile phone networks will facilitate an audio signal bandwidth of 50 Hz-7 kHz. This is suggested since an increased bandwidth will increase the sound quality of the speech signals. Since only few telephones initially will have this facility, a method extending the conventional narrow frequency-band speech signal into a wide-band speech signal utilizing the receiving telephone only is suggested. This will give the impression of a wide-band speech signal. The proposed speech bandwidth extension method is based on models of speech acoustics and fundamentals of human hearing. The extension maps each speech feature separately. Care has been taken to deal with implementation aspects, such as noisy speech signals, speech signal delays, computational complexity, and processing memory usage.

Speech bandwidth extension method and apparatus

A speech bandwidth extension method and apparatus analyzes narrowband speech sampled at 8 kHz using LPC analysis to determine its spectral shape and inverse filtering to extract its excitation signal. The excitation signal is interpolated to a sampling rate of 16 kHz and analyzed for pitch control and power level. A white noise generated wideband signal is then filtered to provide a synthesized wideband excitation signal. The narrowband shape is determined and compared to templates in respective vector quantizer codebooks, to select respective highband shape and gain. The synthesized wideband excitation signal is then filtered to provide a highband signal which is, in turn, added to the narrowband signal, interpolated to the 16 kHz sample rate, to produce an artificial wideband signal. The apparatus may be implemented on a digital signal processor chip.