Wideband Speech Research Articles

AMR 기반 저 전력 인공 대역 확장 기술 개발

대역폭 확장 (Bandwidth Extension)은 300-3400 Hz 대역의 협대역 음성 신호를 50-7000 Hz 대역의 광대역 음성신호로 확장하여 협대역 음성신호의 음질과 명료도를 높이는 기술이다. 본 논문에서는 협대역 음성 정보만을 이용해서 광대역 음성신호를 추정하는 인공 대역폭 확장 기술을 설계하여, ITU-T 협대역 표준 음성 코덱인 AMR (adaptive multi-rate) 복호화기에 내장시킴 (embedded)으로써, 대역폭 확장 모듈에서의 LPC 분석 및 LSP 해석과 관련된 계산량을 감소시켰고, 알고리즘 지연도 줄였다. 그리고 SDS (single distance search) 고속 탐색 방식을 대역폭 확장 시스템의 코드북 매핑에 적용하여, 최종적으로 저 전력 대역 확장 AMR 복호화기를 설계하였다. 제안된 대역폭 확장 방법은 AMR 복호화기 후단에 독립적으로 설치되는 기존 DTE (decode then extend)방식에 비해 28 % 정도의 계산량을 줄이고 알고리즘 지연도 20 msec 줄였다. 또한 제안방식은 피치정보를 이용한 classified 코드북 매핑 방식을 사용하여 스펙트럼 포락선을 확장하였고, 코드 벡터 탐색 시 가중치를 적용하여 광대역 합성 음성의 성능을 향상시켰다. Bandwidth extension is a technique to improve speech quality and intelligibility, extending from 300-3400 Hz narrowband speech to 50-7000 Hz wideband speech. This paper designs an artificial bandwidth extension (ABE) module embedded in the AMR (adaptive multi-rate) decoder, reducing LPC/LSP analysis and algorithm delay of the ABE module. We also introduce a fast search codebook mapping method for ABE, and design a low power BWE technique based on the AMR decoder. The proposed ABE method reduces the computational complexity and the algorithm delay, respectively, by 28 % and 20 msec, compared to the traditional DTE (decode then extend) method. We also introduce a weighted classified codebook mapping method for constructing the spectral envelope of the wideband speech signal.

Predicting the Intelligibility of Vocoded Speech

The purpose of this study is to evaluate the performance of a number of speech intelligibility indices in terms of predicting the intelligibility of vocoded speech. Noise-corrupted sentences were vocoded in a total of 80 conditions, involving three different signal-to-noise ratio levels (-5, 0, and 5 dB) and two types of maskers (steady state noise and two-talker). Tone-vocoder simulations and combined electric-acoustic stimulation (EAS) simulations were used. The vocoded sentences were presented to normal-hearing listeners for identification, and the resulting intelligibility scores were used to assess the correlation of various speech intelligibility measures. These included measures designed to assess speech intelligibility, including the speech transmission index (STI) and articulation index based measures, as well as distortions in hearing aids (e.g., coherence-based measures). These measures employed primarily either the temporal-envelope or the spectral-envelope information in the prediction model. The underlying hypothesis in the present study is that measures that assess temporal-envelope distortions, such as those based on the STI, should correlate highly with the intelligibility of vocoded speech. This is based on the fact that vocoder simulations preserve primarily envelope information, similar to the processing implemented in current cochlear implant speech processors. Similarly, it is hypothesized that measures such as the coherence-based index that assess the distortions present in the spectral envelope could also be used to model the intelligibility of vocoded speech. Of all the intelligibility measures considered, the coherence-based and the STI-based measures performed the best. High correlations (r = 0.9 to 0.96) were maintained with the coherence-based measures in all noisy conditions. The highest correlation obtained with the STI-based measure was 0.92, and that was obtained when high modulation rates (100 Hz) were used. The performance of these measures remained high in both steady-noise and fluctuating masker conditions. The correlations with conditions involving tone-vocoded speech were found to be a bit higher than the correlations with conditions involving EAS-vocoded speech. The present study demonstrated that some of the speech intelligibility indices that have been found previously to correlate highly with wideband speech can also be used to predict the intelligibility of vocoded speech. Both the coherence-based and STI-based measures have been found to be good measures for modeling the intelligibility of vocoded speech. The highest correlation (r = 0.96) was obtained with a derived coherence measure that placed more emphasis on information contained in vowel/consonant spectral transitions and less emphasis on information contained in steady sonorant segments. High (100 Hz) modulation rates were found to be necessary in the implementation of the STI-based measures for better modeling of the intelligibility of vocoded speech. We believe that the difference in modulation rates needed for modeling the intelligibility of wideband versus vocoded speech can be attributed to the increased importance of higher modulation rates in situations where the amount of spectral information available to the listeners is limited (eight channels in our study). Unlike the traditional STI method that has been found to perform poorly in terms of predicting the intelligibility of processed speech wherein nonlinear operations are involved, the STI-based measure used in the present study has been found to perform quite well. In summary, the present study took the first step in modeling the intelligibility of vocoded speech. Access to such intelligibility measures is of high significance as they can be used to guide the development of new speech coding algorithms for cochlear implants.

Algorithms and Software for Predictive and Perceptual Modeling of Speech

From the early pulse code modulation-based coders to some of the recent multi-rate wideband speech coding standards, the area of speech coding made several significant strides with an objective to attain high quality of speech at the lowest possible bit rate. This book presents some of the recent advances in linear prediction (LP)-based speech analysis that employ perceptual models for narrow- and wide-band speech coding. The LP analysis-synthesis framework has been successful for speech coding because it fits well the source-system paradigm for speech synthesis. Limitations associated with the conventional LP have been studied extensively, and several extensions to LP-based analysis-synthesis have been proposed, e.g., the discrete all-pole modeling, the perceptual LP, the warped LP, the LP with modified filter structures, the IIR-based pure LP, all-pole modeling using the weighted-sum of LSP polynomials, the LP for low frequency emphasis, and the cascade-form LP. These extensions can be classified as algorithms that either attempt to improve the LP spectral envelope fitting performance or embed perceptual models in the LP. The first half of the book reviews some of the recent developments in predictive modeling of speech with the help of Matlab™ Simulation examples.

적응적인 확장된 코드북을 이용한 분할 벡터 양자화기 구조의 ISF 양자화기 개선

본 논문에서는 ISF 계수의 순서화 성질을 이용하여 분할구조 벡터양자화기의 단점을 보완하여 ISF 계수 양자화의 성능을 높이는 알고리듬을 제안하고, 이를 이용한 광대역 음성 부호화기용 ISF 계수 양자화기를 설계한다. 16차 이상의 광대역 코덱의 ISF 계수는 계산량과 메모리 사용을 줄이기 위해서 분할구조의 벡터 양자화기를 사용한다. 분할구조 양자화기는 ISF 계수간의 상관도를 충분히 활용하지 못하는 단점이 발생한다. 제안하는 알고리듬은 이러한 단점을 극복하기 위하여 ISF 계수의 순서화 성질을 이용한다. ISF 계수의 순서화 성질을 이용하여 각 서브벡터의 불필요한 코드북 (Codebook Redundancy)을 검색할 수 있다. 이러한 불필요한 코드북은 ISF 계수의 순서화 성질, ISF 계수 예측과정과 기존 코드북의 보간법 (Interpolation)을 통해 적응적인 확장된 코드북으로 교체되어 양자화기의 성능을 향상시킨다. 제안된 알고리듬은 기존의 분할구조 양자화기에서 사용되지 못했던 17 %가량의 불필요한 코드북 인덱스를 적응적인 확장된 코드북에 할당하여, 표준화된 코덱인 AMR-WB의 ISF 계수 양자화기에 비해서 주파수 왜곡 관점에서 약 2 bit 가량의 이득을 보는 결과를 얻었다. This paper presents a method for improving the performance of ISF coefficients quantizer through compensating the defect of the split structure vector quantization using the ordering property of ISF coefficients. And design the ISF coefficients quantizer for wideband speech codec using proposed method. The wideband speech codec uses split structure vector quantizer which could not use the correlation between ISF coefficients fully to reduce complexity and the size of codebook. The proposed algorithm uses the ordering property of ISF coefficients to overcome the defect. Using the ordering property, the codebook redundancy could be figured out. The codebook redundancy is replaced by the adaptive-extended codebook to improve the performance of the quantizer through using the ordering property, ISF coefficient prediction and interpolation of existing codebook. As a result, the proposed algorithm shows that the adaptive-extended codebook algorithm could get about 2 bit gains in comparison with the existing split structure ISF quantizer of AMR-WB (G.722.2) in the points of spectral distortion.

Double-Ended Quality Assessment System for Super-Wideband Speech

This paper describes a double-ended quality assessment system for speech with a bandwidth of up to 14 kHz (so-called super-wideband speech). The quality assessment system is based on a combination of local and global features, where the local features are dependent on a time alignment procedure and the global features are not. The system is evaluated over a large set of subjectively scored narrowband, wideband and super-wideband speech databases. The system performs similarly to PESQ for narrowband speech and significantly better for wideband speech.

Intra- and inter-frame prediction in bandwidth scalable coding of wideband speech

This study discusses a predictive coding scheme that utilises both the intra-frame correlation (here referred to as redundancy between frequency bands) and inter-frame correlation in bandwidth scalable coding of wideband speech. Prediction error filters that combine intra-frame prediction with inter-frame prediction in a cascade connection are examined. Three representative intra-frame functions that have been developed in the area of bandwidth extension (BWE) are considered to see how well they exploit the intra-frame correlation. In addition, some resulting changes are investigated when they are combined with the predictive vector quantiser that exploits the inter-frame correlation. The performances of the Gaussian mixture model-based and hidden Markov model-based BWE functions are similar in the context of intra-frame coding, but both of them significantly outperform the linear BWE function in the same context. However, it is also observed that the linear function is the most promising in the context of the joint predictive coding of intra-frame and inter-frame. These results are supported by some statistical tests.

A Bandwidth Extension Scheme for G.711 Speech by Embedding Multiple Highband Gains

We present an improvement to the existing steganography-based bandwidth extension scheme. Enhanced WB (wideband) speech quality is achieved by embedding multiple highband spectral gains into a G.711 bitstream. The number of spectral gains is selected by optimizing the quantity of the embedding data with respect to the quality of the extended WB speech. Compared to the existing method, the proposed scheme improves the WB PESQ (Perceptual Evaluation of Speech Quality) score by 0.334 with negligible degradation of the embedded narrowband speech.

Particle Filter Enhancement of Speech Spectral Amplitudes

This paper presents a particle filter approach to spectral amplitude speech enhancement. Spectral amplitudes are known to exhibit inter-frame dependencies and non-Gaussian statistics; however, incorporating these properties makes closed-form solutions intractable. Using the particle filter framework allows the presented algorithm to model the speech spectral amplitudes as an autoregressive process with Laplace distributed excitation. Two variants of the standard algorithm are also presented: one that uses an interacting multiple model approach to account for transitions between active speech and silence intervals, and one that allows for phase differences between the clean speech and noise complex Fourier transform coefficients. All of the particle sampling distributions are constrained to take the measurement into account, improving sampling efficiency. In experiments using wideband speech and real recorded noise the proposed algorithm variants are shown to offer natural-sounding output speech, with objective evaluation results that compare favorably to existing particle filter speech enhancement algorithms. The multiple model variant is found to improve inter-speech noise reduction, while the phase variant improves performance when the signal-to-noise ratio is low.

Quality Dimensions of Narrowband and Wideband Speech Transmission

The study presented in this paper aims at exploring the perceptual spaces evoked for users of two different telephone scenarios: traditional narrowband speech transmission, and mixed narrowband/wideband speech transmission that may be encountered in today's Voice-over-IP services. Underlying dimensions that constitute the skeleton of these spaces are revealed by auditory experiments, following two different paradigms of judgment: a) Similarity-scaling, and b) Attribute-scaling (Semantic Differential) with subsequent a) Multidimensional Scaling, and b) Principal Component Analysis of a diverse set of stimuli. Similar configurations are obtained which are unequivocally interpretable. Three common dimensions, valid for both the narrowband and the wideband scenario can be identified: Discontinuity, Noisiness, and Coloration. In addition, the wideband space is extended by a further, wideband-specific dimension. Integral listening-quality can well be modeled by means of these dimensions. In both scenarios, Discontinuity represents the most important quality feature. The presented work forms the basis for instrumental diagnostic quality measures.

Two-Dimensional FIR Filter Design on Wideband Speech Enhancement in Microphone Array

Due to complexity of sound environment, the performance of speech enhancement is degraded greatly based on traditional beam-forming when directivity of arrival of sound and number of sound are not been estimated precisely. In this paper, according to characteristics of handle-communicated equipment, a method on suppression of environmental noise and disturbance is provided. Beam-forming on speech wideband in desired angle is realized by designing a two-dimensional FIR filter which has fan structure in pass-band and wedge-shaped structure in transition-band. The filter can suppress noise and disturbance out of main-lobe desired. The simulations demonstrated that the filter designed is effective.

Objective and subjective speech quality evaluation of wideband noise reduction algorithms.

Subjective and/or objective measurements of speech quality are important in benchmarking speech enhancement algorithms. Subjective measures include ratings of speech quality by listeners, whereas objective measures compute a metric based on the clean and enhanced speech samples. While subjective quality ratings are the “gold‐standard,” they are also time‐ and resource‐consuming. An objective metric that correlates highly with subjective data is attractive, as it can act as a substitute for benchmarking and fine‐tuning the noise reduction algorithms. In this paper, the performance of several noise reduction algorithms for wideband (50–7000 Hz) telephony application was evaluated both subjectively and objectively. A custom wideband noise reduction database was created that contained speech samples corrupted by different background noises at different signal to noise ratios and processed by seven different noise reduction algorithms. Speech samples in the database were subsequently rated by a group of 32 listeners with normal hearing capabilities. Several objective metrics including log‐likelihood ratio, weighted spectral slope, PESQ, and the loudness pattern distortion (LPD) measure based on the Moore–Glasberg auditory model were used to predict the subjective ratings. Results showed that the subjective ratings were highly reliable and the LPD metric correlated the best with subjective ratings of enhanced wideband speech.

Discrete cosine transform particle filter speech enhancement

A discrete cosine transform (DCT) domain speech enhancement algorithm is proposed that models the evolution of speech DCT coefficients as a time-varying autoregressive process. Rao-Blackwellized particle filter (RBPF) techniques are used to estimate the model parameters and recover the clean signal coefficients. Using very low-order models for each coefficient and operating at a decimated frame rate, the proposed approach provides a significant complexity reduction compared to the standard full-band RBPF speech enhancement algorithm. In addition to the complexity gains, performance is also improved. Modeling the speech signal in the DCT-domain is shown to provide a better fit in spectral troughs, leading to more noise reduction and less speech distortion. To illustrate possible frequency-dependent processing strategies, a hybrid structure is proposed that offers a complexity/performance trade-off by substituting a simple DCT Wiener filter for the DCT-RBPF in some bands. In comparisons with high performing speech enhancement algorithms using wideband speech and noise, the proposed DCT-RBPF algorithm achieves higher scores on objective quality and intelligibility measures.

Optimized Subvector Processing in Split Vector Quantization

Split vector quantization (SVQ) is efficient but suboptimal. Here a renormalization process is proposed for intraframe splitting and joining of subvectors, which integrates gracefully with trained interframe prediction. Renormalization increases the availability of codevectors for the quantization of each subvector in ordered vectors such as the line spectral frequency (LSF) vectors. For 16-dimensional LSF vectors from wideband speech, renormalized SVQ (RSVQ) is shown to achieve a savings of 4 bit/frame over standard SVQ, reaching transparent coding at 42 bit/frame. Further, predictive RSVQ saves an additional 4 bit/frame for transparent coding down to 38 bit/frame.

Instrumental Estimation of E-Model Parameters for Wideband Speech Codecs

A method is described for quantifying the quality of wideband speech codecs. Two parameters are derived from signal-based speech quality model estimations: (i) a wideband equipment impairment factor Ie,WB and (ii) a wideband packet-loss robustness factor Bpl, WB. The equipment impairment factor can be combined with impairment factors for other quality degradations to form an estimate of the overall conversational quality R of a wideband communication scenario, using a wideband extension of the E-model. The packet-loss robustness factor captures the robustness of the codec against packet-loss degradations. In contrast to past work, these parameters are no longer determined on the basis of auditory test results, but from signal-based speech quality models. We applied three intrusive models to several databases and compared the derived quality estimates and impairment factors to those obtained from auditory tests. The results show that when migrating from narrowband to wideband transmission--a quality improvement of roughly 30% can be obtained, which is very similar to the one observed in auditory tests. The estimated impairment factors show a high correlation to those derived from auditory scores. Congruences and discrepancies to auditory test results are discussed, and an outline of work necessary to set up a wideband or even superwideband E-model is given.

ITU-T G.711.1: extending G.711 to higher-quality wideband speech

In March 2008 the ITU-T approved a new wideband speech codec called ITU-T G.711.1. This Recommendation extends G.711, the most widely deployed speech codec, to 7 kHz audio bandwidth and is optimized for voice over IP applications. The most important feature of this codec is that the G.711.1 bitstream can be transcoded into a G.711 bitstream by simple truncation. G.711.1 operates at 64, 80, and 96 kb/s, and is designed to achieve very short delay and low complexity. ITU-T evaluation results show that the codec fulfils all the requirements defined in the terms of reference. This article presents the codec requirements and design constraints, describes how standardization was conducted, and reports on the codec performance and its initial deployment.

Improved voice activity detection algorithm using wavelet and support vector machine

This paper proposes an improved voice activity detection (VAD) algorithm using wavelet and support vector machine (SVM) for European Telecommunication Standards Institution (ETSI) adaptive multi-rate (AMR) narrow-band (NB) and wide-band (WB) speech codecs. First, based on the wavelet transform, the original IIR filter bank and pitch/tone detector are implemented, respectively, via the wavelet filter bank and the wavelet-based pitch/tone detection algorithm. The wavelet filter bank can divide input speech signal into several frequency bands so that the signal power level at each sub-band can be calculated. In addition, the background noise level can be estimated in each sub-band by using the wavelet de-noising method. The wavelet filter bank is also derived to detect correlated complex signals like music. Then the proposed algorithm can apply SVM to train an optimized non-linear VAD decision rule involving the sub-band power, noise level, pitch period, tone flag, and complex signals warning flag of input speech signals. By the use of the trained SVM, the proposed VAD algorithm can produce more accurate detection results. Various experimental results carried out from the Aurora speech database with different noise conditions show that the proposed algorithm gives considerable VAD performances superior to the AMR-NB VAD Options 1 and 2, and AMR-WB VAD.

Frequency-Domain Pearson Distribution Approach for Independent Component Analysis (FD-Pearson-ICA) in Blind Source Separation

<para xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> In frequency-domain blind source separation (BSS) for speech with independent component analysis (ICA), a practical parametric Pearson distribution system is used to model the distribution of frequency-domain source signals. ICA adaptation rules have a score function determined by an approximated signal distribution. Approximation based on the data may produce better separation performance than we can obtain with ICA. Previously, conventional hyperbolic tangent <formula formulatype="inline"><tex Notation="TeX">$(tanh)$</tex> </formula> or generalized Gaussian distribution (GGD) was uniformly applied to the score function for all frequency bins, even though a wideband speech signal has different distributions at different frequencies. To deal with this, we propose modeling the signal distribution at each frequency by adopting a parametric Pearson distribution and employing it to optimize the separation matrix in the ICA learning process. The score function is estimated by the appropriate Pearson distribution parameters for each frequency bin. We devised three methods for Pearson distribution parameter estimation and conducted separation experiments with real speech signals convolved with actual room impulse responses <formula formulatype="inline"><tex Notation="TeX">$(T_{60}=130\ {\hbox {ms}})$</tex></formula>. Our experimental results show that the proposed frequency-domain Pearson-ICA (FD-Pearson-ICA) adapted well to the characteristics of frequency-domain source signals. By applying the FD-Pearson-ICA performance, the signal-to-interference ratio significantly improved by around 2–3 dB compared with conventional nonlinear functions. Even if the signal-to-interference ratio (SIR) values of FD-Pearson-ICA were poor, the performance based on a disparity measure between the true score function and estimated parametric score function clearly showed the advantage of FD-Pearson-ICA. Furthermore, we confirmed the optimum of the proposed approach for/optimized the proposed approach as regards separation performance. By combining individual distribution parameters directly estimated at low frequency with the appropriate parameters optimized at high frequency, it was possible to both reasonably improve the FD-Pearson-ICA performance without any significant increase in the computational burden by comparison with conventional nonlinear functions. </para>

Effect of bandwidth extension to telephone speech recognition in cochlear implant users

The present study investigated a bandwidth extension method to enhance telephone speech understanding for cochlear implant (CI) users. The acoustic information above telephone speech transmission range (i.e., 3400 Hz) was estimated based on trained models describing the relation between narrow-band and wide-band speech. The effect of the bandwidth extension method was evaluated with IEEE sentence recognition tests in seven CI users. Results showed a relatively modest but significant improvement in the speech recognition with the proposed method. The effect of bandwidth extension method was also observed to be highly dependent on individual CI users.

Low-Complexity Wideband LSF Quantization Using Algebraic Trellis VQ

In this paper an algebraic trellis vector quantization (ATVQ) that introduces algebraic codebooks into trellis coded vector quantization (TCVQ) structure is presented. Low encoding complexity and minimum memory storage requirements are achieved using the proposed approach. It exploits advantages of both the TCVQ and the algebraic codebooks to know the delayed decision, the codebook widening, the low computational complexity and the no storage of codebook. This novel vector quantization scheme is used to encode the wideband speech line spectral frequencies (LSF) parameters. Experimental results on wideband speech have shown that ATVQ yields the same performance as the traditional split vector quantization (SVQ) and the TCVQ in terms of spectral distortion (SD). It can achieve a transparent quality at 47bits/frame with a considerable reduction of memory storage and computation complexity when compared to SVQ and TCVQ.

Iterative AMR-WB Source and Channel Decoding Using Differential Space–Time Spreading-Assisted Sphere-Packing Modulation

In this paper, we present a novel system that invokes jointly optimized iterative source and channel decoding for enhancing the error resilience of the adaptive multirate wideband (AMR-WB) speech codec. The resultant AMR-WB-coded speech signal is protected by a recursive systematic convolutional (RSC) code and transmitted using a noncoherently detected multiple-input-multiple-output (MIMO) differential space-time spreading (DSTS) scheme. To further enhance the attainable system performance and to maximize the coding advantage of the proposed transmission scheme, the system is also combined with multidimensional sphere-packing (SP) modulation. Furthermore, the convergence behavior of the proposed scheme is evaluated with the aid of extrinsic information transfer (EXIT) charts. The proposed system exhibits an <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Eb</i> / <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">N</i> <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">0</sub> gain of about 1 dB, as compared with the benchmark scheme carrying out joint channel decoding and DSTS-aided SP demodulation in conjunction with separate AMR-WB decoding, when using only <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">I</i> <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">system</sub> = 2 system iterations and when communicating over narrow-band correlated Rayleigh fading channels.