Until recently, there was no emotional speech dataset available in Canadian French. This was a limiting factor for research activities not only in Canada, but also elsewhere. This paper introduces the newly released Canadian French Emotional (CaFE) speech dataset and gives details about its design and content. This dataset contains six different sentences, pronounced by six male and six female actors, in six basic emotions plus one neutral emotion. The six basic emotions are acted in two different intensities. The audio is digitally recorded at high-resolution (192 kHz sampling rate, 24 bits per sample). This new dataset is freely available under a Creative Commons license (CC BY-NC-SA 4.0).

One of the most common yet detrimental compression artifacts in frequency-domain audio codecs is known as pre-echo, which is perceived as a brief noise preceding transient signals, and is discernable even without direct comparison to the original signal. Because of its substantial negative impact on audio quality, many techniques have been proposed to alleviate it, but not without effect on coding efficiency. This paper presents a novel method to reduce pre-echo noise using only information already available at the decoder, such as scale-factors, that allow an estimation of the quantization noise levels in each frequency band. Doing so allows the proposed method to reduce pre-echo noise based on a precise modeling of the quantization noise spread before the transient signal. This has shown to improve both the subjective and objective quality of the MPEG AAC codec, and requires no modifications to the existent standard-compliant encoders.

Although emotions play a major role in voice communication, the quality of their reproduction by low bit rate voice coders has never been investigated so far. This paper shows that the emotional state of a speaker can be identified automatically, with reasonable precision and accuracy, using conventional voice coding parameters (pitch, voicing, energy and LPC coefficients). It also shows that the performance of this identification degrades when these parameters are quantized, especially at lower rates (1200 bits/s). This suggests that quantization of speech parameters could be improved by targeting the faithful reproduction of important higher-level voice communication attributes such as emotions, rather than simply optimizing objective measures such as the signal-to-noise ratio, mean squared error and spectral distortion.

Stop consonants are an important constituent of the speech signal. They contribute significantly to its intelligibility and subjective quality. However, because of their dynamic and unpredictable nature, they tend to be difficult to encode using conventional approaches such as linear predictive coding and transform coding. This paper presents a system to detect, segment, and modify stop consonants in a speech signal. This system is then used to assess the following hypothesis: Muting the burst phase of stop consonants has a negligible impact on the subjective quality of speech. The muting operation is implemented and its impact on subjective quality is evaluated on a database of speech signals. The results show that this apparently drastic alteration has in reality very little perceptual impact. The implications for speech coding are then discussed.

This paper presents a lossless compression algorithm for the binary indices of the embedded algebraic vector quantizer (EAVQ) used by the AMR-WB (Extended Adaptive Multi-Rate Wide Band) codec. We present a statical study of the EAVQ indices for diverse audio types (speech, music, etc.) and we discuss the design of the lossless algorithm including the choice of different strategies. The proposed algorithm combines run length encoding (RLE) and context-based arithmetic encoding to reduce the bitrate of the EAVQ indices by about 10% at the expense of 1% rise in complexity of the codec. The proposed algorithm can increase the segmental signal to noise ratio of about 9% at low rates for speech signals and improve the subjective scores in noisy channels by about 0.5 on a five-point scale if combined with an additional protection layer.

Traditionally, speech coding and audio coding were separate worlds. Based on different technical approaches and different assumptions about the source signal, neither of the two coding schemes could efficiently represent both speech and music at low bitrates. This paper presents a unified speech and audio codec, which efficiently combines techniques from both worlds. This results in a codec that exhibits consistently high quality for speech, music and mixed audio content. The paper gives an overview of the codec architecture and presents results of formal listening tests comparing this new codec with HE-AAC(v2) and AMR-WB+. This new codec forms the basis of the reference model in the ongoing MPEG standardization activity for Unified Speech and Audio Coding.

In this paper we present a novel technique to enhance music signals encoded using a low bit rate CELP coder. The method is based on reduction of inter-tone quantization noise for decoded music signals without affecting the quality for speech signals. The proposed technique consists of two modules. The first module is used to discriminate between stable tonal sounds and other sounds and the second module is used to reduce the inter-tone quantization noise in the stable tonal segments. The inter-tone noise is reduced by means of spectral subtraction. The proposed method is a part of the newly standardised ITU-T G.718 codec.

This paper presents a new approach for accurate detection of voiced onsets in a speech signal. The knowledge of the precise location of the beginning of a voiced segment has several potential applications in speech compression (e.g. source-controlled variable bitrate coding, classification-based frame erasure concealment). The proposed onset detection algorithm is based on Teager's energy operator applied on sub-bands. The technique has been integrated in the signal classifier of the VMR-WB speech coding standard used for frame erasure (FE) concealment. A subjective listening test using MUSHRA methodology showed an improvement in frame error conditions with respect to the legacy VMR-WB classification.

Error propagation after a frame loss is an important factor in quality degradation for predictive speech coders. This is mainly due to the lack of synchronization in the adaptive codebook in the good frames following a frame erasure. This article presents a method for resynchronizing the glottal pulse after an erased frame. The method uses an extra frame delay at the decoder, and can be applied with or without additional side information. The approach has been implemented in the G.729.1 standard and results in improved decoder convergence after erased frames. Subjective tests have demonstrated that this improves perceived quality in the presence of frame erasures.

The adaptive codebook used in code-excited linear prediction (CELP)-like speech codecs is very effective for modeling the quasi-periodic component of the excitation signal but, unfortunately, introduces a strong interframe dependency that renders the decoder vulnerable to frame erasures. For voiced speech, the error affects not only the erased frame but also all the subsequent frames. In this paper, a technique to improve the recovery after a frame erasure is proposed. The technique consists in a constrained excitation search at the encoder and a resynchronization procedure at the decoder. The constraint aims at reducing the contribution of the adaptive codebook by making the innovation codebook partially model the pitch excitation. Further, for highly voiced frames, the pitch-related information contained in the innovation excitation is exploited at the decoder to speed up the resynchronization of the adaptive codebook after a frame erasure. When applied to the adaptive multirate wideband (AMR-WB) codec, the method brings a significant improvement in the case of frame erasures, at the cost of a minor quality loss compared to the standard codec at the same bit rate. The method does not need additional delay and has the advantage of maintaining full interoperability between the standard codec and its modified version.

The adaptive codebook used in CELP (code excited linear prediction) codecs to model the pitch excitation allows the attainment of a high quality of synthesized speech but introduces a strong inter-frame dependency and consequently causes error propagation in case of frame erasure. In a previous work we showed that the error propagation can be greatly reduced by constraining, at the encoder side, the innovative codebook to partially model the pitch excitation. In this paper we extend this work by exploiting, at the decoder side, the pitch-related information present in the innovative excitation to speed up the recovery of the decoder. The method consists in adequately shifting the last pitch pulse present within the corrupted adaptive codebook memory so that it is resynchronized with the excitation parameters of the frame that follows the erased one

Pure estimation in bandwidth extension of bandlimited speech does not provide transparent quality in the extended band. Combining coding and estimation of the missing band can achieve higher quality by transmitting additional information. However, substantial artifacts can remain in the extended band. In this paper, we introduce a new postfiltering designed to reduce these artifacts. Based on a source-filter model, the adopted bandwidth extension transmits spectral envelope parameters, while estimates the excitation at the receiver. The perceptual quality is then enhanced by processing the estimated excitation by a short-term and a long-term postfilter. Objective and subjective assessments show substantial gains when using the new postfiltering. It confirms that low bit-rate wideband coding based on bandwidth extension can get closer to the performances of the single band wideband coders

We consider the problem of separating instantaneous mixtures of different sound sources in multi-channel audio signals. Several methods have been developed to solve this problem. Independent component analysis (ICA) is certainly the most known method and the most used. ICA exploits the non-Gaussianity of the sources in the mixtures. In this study, we propose an improved signal separation algorithm where simultaneously we increase the non-Gaussian nature of signals and we initiate the preliminary separation. For this, the observations are transformed into an adequate representation using the wavelet packets decomposition. In this study, we consider the instantaneous mixture of two sources using two sensors. We validate our approach by using synthetic and recorded audio signals. Preliminary results show a strong improvement when compared to conventional ICA (FastICA), with specific signals.

We propose in this paper a two-stage lossless audio coder for stereo signals. The first stage is based on a hybrid approach that uses either a stereo linear prediction or a multilayer perceptron-based (MLP) nonlinear prediction. The second stage is based on two cascaded normalized least mean square (NLMS) filters that remove the remaining redundancy in the residuals of the stereo prediction. The obtained compression ratios are equal or superior to the best state-of-the-art coders

Achieving real-time voice communication over a mobile wireless ad hoc network poses many challenges both in speech coding and network protocols. In this paper, we investigate the real-time voice transmission capacity of ad hoc networks using a multiple description coding (MDC) scheme along with a new multi-path routing protocol called MSBR. The MDC generates two or more complementary bitstreams from the bitstream of the speech encoder, each sent along different routes. This allows the receiver to maintain acceptable speech quality even with missing packets. MSBR algorithm attempts to find multiple reliable stable routes to the destination node. Simulations using the GloMoSim network simulator and speech audio evaluation setups were used to study the performances of the approach in different network scenarios. Results show that the MDC scheme, together with MSBR, makes an effective use of the network and provides good performances for real time voice transmission

This paper presents a hybrid audio coding algorithm integrating an LP-based coding technique and a more general transform coding technique. ACELP is used in LP-based coding mode, whereas algebraic TCX is used in transform coding mode. The algorithm extends previously published work on ACELP/TCX coding in several ways. The frame length is increased to 80 ms, adaptive multi-length sub-frames are used with overlapping windowing, an extended multi-rate algebraic VQ is applied to the TCX spectrum to avoid quantizer saturation, and noise shaping is improved. Results show that the proposed hybrid coder has consistently high performance for both speech and music signals.

The adaptive codebook used in CELP-like speech coders is extremely effective on voiced signals. Unfortunately, it is also the main source of error propagation at the decoder when a frame is lost. In this paper, we study several ways of limiting the energy contribution of the adaptive codebook to the synthesized speech signal. We show that a constrained search of the adaptive and innovative codebooks significantly improves the recovery time of the decoder after a lost frame, at the cost of only minor quality degradation in a clear channel. When applied to a standard codec such as the AMR-WB, this constraint only affects the encoder, and the modified codec remains fully interoperable with the standard codec.

Speech coders provide high speech quality at low rates. However they perform poorly when encoding non-speech signals. This paper proposes a new enhancement algorithm requiring minimum side information to reduce the effect of this shortcoming. The enhancement algorithm consists of post-processing the speech decoder output in the spectral domain. Specifically, some frequency components are reduced or forced to zero when the corresponding frequency content is poorly described by the speech coder. The choice of modifying spectral components is determined at the encoder, thus requiring us to transmit the decision information. Experiments combining the AMR-WB speech codec and the proposed audio enhancement show that the quality for music signals is improved significantly while not affecting the quality for speech inputs.

We present an objective and subjective comparison of alternative methods for improving the robustness of speech coders in packet networks. The two approaches are considered: 1) adding redundancy in the packets to improve the robustness of a baseline encoder; 2) reducing (or eliminating) inter-frame dependencies at the encoder. It is shown that both approaches have to trade bit rate and/or delay for quality over lossy channels. Formal subjective tests clearly show that, using relatively simple forward error correction methods, standard coders such as ITU-T recommendation G.729 can be made significantly more robust than "frame-independent" coders, at a lower or similar bit rate.

We present a new method, called Voronoi extension, for the design of low-complexity multi-rate lattice vector quantization (VQ). With this technique, lattice codebooks of arbitrarily large bit rates can be generated algorithmically and the problem of lattice codebook overload can be bypassed. We describe a practical multi-rate quantization system based on Voronoi extension and derived from the lattice RE/sub 8/. This system is applied to the TCX coding model using pitch prediction, so as to extend AMR-WB speech coding at high bit rates (in particular 32 kbit/s).

The paper presents a method to improve the recovery of a speech decoder after the reception of one or several late frames. Rather than considering a late frame as "lost", we propose to use it in order to update the internal state of the decoder. This limits, and, in some cases, stops, the error propagation caused by the concealment. Evaluation results show that there is much to be gained in a voice over IP environment, where late frames can be used to improve the robustness against jitter without increasing the overall end-to-end delay.

We consider a special case of Voronoi coding, where a lattice /spl Lambda/ in /spl Ropf//sup n/ is shaped (or truncated) using a lattice /spl Lambda/'={(m/sub 1/x/sub 1/,...,m/sub n/x/sub n/)|(x/sub 1/,...,x/sub n/)/spl isin//spl Lambda/} for a fixed m_=(m/sub 1/,...,m/sub n/)/spl isin/(/spl Nopf//spl bsol/{0,1})/sup n/. Using this technique, the shaping boundary is near-ellipsoidal. It is shown that the resulting codes can be indexed by standard Voronoi indexing algorithms plus a conditional modification step, as far as /spl Lambda/' is a sublattice of /spl Lambda/. We derive the underlying conditions on m_ and present generic near-ellipsoidal Voronoi indexing algorithms. Examples of constraints on m_ and conditional modification are provided for the lattices A/sub 2/, D/sub n/ (n/spl ges/2) and 2D/sub n//sup +/ (n even /spl ges/4).

This paper describes the adaptive multirate wideband (AMR-WB) speech codec selected by the Third Generation Partnership Project (3GPP) for GSM and the third generation mobile communication WCDMA system for providing wideband speech services. The AMR-WB speech codec algorithm was selected in December 2000 and the corresponding specifications were approved in March 2001. The AMR-WB codec was also selected by the International Telecommunication Union-Telecommunication Sector (ITU-T) in July 2001 in the standardization activity for wideband speech coding around 16 kb/s and was approved in January 2002 as Recommendation G.722.2. The adoption of AMR-WB by ITU-T is of significant importance since for the first time the same codec is adopted for wireless as well as wireline services. AMR-WB uses an extended audio bandwidth from 50 Hz to 7 kHz and gives superior speech quality and voice naturalness compared to existing second- and third-generation mobile communication systems. The wideband speech service provided by the AMR-WB codec will give mobile communication speech quality that also substantially exceeds (narrowband) wireline quality. The paper details AMR-WB standardization history, algorithmic description including novel techniques for efficient ACELP wideband speech coding and subjective quality performance of the codec.

We present in this paper new methods for achieving high- quality wideband speech at low rates using the ACELP algorithm. Several innovations are introduced to optimize the quality and minimize the complexity of the coder. A multi-rate wideband speech encoding algorithm based on these techniques was recently selected by 3GPP as the standard for AMR-WB, and is currently one of the candidates for the ITU- T wideband speech coder standard at around 16 kbit/sec. This standard was jointly developed by VoiceAge and Nokia.

The Third Generation Partnership Project (3GPP) and European Telecommunications Standards Institute (ETSI) have carried out development and standardisation of a wideband speech codec for GSM and the third generation mobile communication WCDMA system since 1999. The Adaptive Multi-Rate Wideband (AMR-WB) codec algorithm was selected in December 2000, and the corresponding specifications were approved in March 2001. The AMR-WB codec was jointly developed by Nokia and VoiceAge. AMRWB extends the audio bandwidth from 3.4 kHz to 7 kHz and gives superior speech quality and voice naturalness compared to existing 2nd and 3rd generation mobile communication systems. The wideband speech service provided by the AMRWB codec will give mobile communication speech quality that even exceeds (narrowband) wireline quality.

We present the performance of several suboptimal algebraic quantizers in 24 dimensions. The Gaussian source is encoded at 1/2 bit per sample using the binary extended Golay code C/sub 24/ and the hexacode H/sub 6/. We also propose two new suboptimal decoding algorithms for the hexacode H/sub 6/.

This paper describes a fixed-rate quantizer using algebraic techniques as well as conventional stored codebooks to represent the wideband line spectral frequencies (LSF). It is based on two-stage split vector quantization with random and lattice codebooks in the first and second stage, respectively. We investigate the use of variable bit allocation in lattice quantization in order to capture outliers and reduce the overload distortion in spectral quantization, particularly for non-speech signals. Experimental results show that a variable bit allocation in split quantization yields performances slightly better than a fixed allocation at the same rate.

In this paper, we present a new approach to shape the coding noise in speech and audio coders. The approach, called spectral amplitude warping (SAW), consists essentially of a pre- and post-processing which apply a nonlinear transformation to the signal short-term spectrum prior to, and after, encoding. Since it is possible to view SAW as a separate entity from the coder, the noise shaping capability of an existing coder can be improved without modifying the coder itself. Using SAW as a pre- and post-process to the G.722 wideband speech coding standard, it was found in an informal listening test that the quality of the 64 kb/s operating mode can be achieved at only 48 kb/s. The price to be paid is an additional delay.

This paper reports on the specific contribution of the wavelet transform (WT) in the TCX coding model for audio signals. TCX, or "transform coded excitation", is a frame based coding algorithm that uses both time domain (linear prediction) and frequency domain (transform coding) approaches to exploit signal redundancies as well as frequency masking. While previous work on TCX used the discrete Fourier transform (DFT), the quality for highly non-stationary signals such as percussions was less than satisfactory. The WT has therefore been investigated as compromise between time and frequency resolution.

This paper describes the application of transform coded excitation (TCX) coding to encoding wideband speech and audio signals in the bit rate range of 16 kbits/s to 32 kbits/s. The approach uses a combination of time domain (linear prediction; pitch prediction) and frequency domain (transform coding; dynamic bit allocation) techniques, and utilizes a synthesis model similar to that of linear prediction coders such as CELP. However, at the encoder, the high complexity analysis-by-synthesis technique is bypassed by directly quantizing the so-called target signal in the frequency domain. The innovative excitation is derived at the decoder by inverse filtering the quantized target signal. The algorithm is intended for applications whereby a large number of bits is available for the innovative excitation. The TCX algorithm is utilized to encode wideband speech and audio signals with a 50-7000 Hz bandwidth. Novel quantization procedures including inter-frame prediction in the frequency domain are proposed to encode the target signal. The proposed algorithm achieves very high quality for speech at 16 kbits/s, and for music at 24 kbits/s.>