Mixed Excitation Linear Prediction Research Articles

Implementation and evaluation of low-speed speech compression LPC and MELP algorithms

Abstract— Currently, the design of a speech signal compression module that responds to low speed but still ensures signal quality for communication devices is a topic of interest for research. LPC (Linear Prediction Coding) and MELP (Mixed-Excitation Linear Prediction), two common approaches, are extensively researched and used, particularly in the vocoder of radio communication equipment like HF or VHF equipment. Implementing security solutions for these devices are challenging due to the crucial role played by the vocoder in signal processing prior to encryption. The paper first analyzes the two algorithms LPC and MELP and implements them on the current popular hardware technologies ARM and DSP to give an evaluation direction when choosing technology to serve the design of vocoders. There are many different methods of speech quality assessment in this paper, the PESQ method according to the ITU-T P862 standard was used to evaluate the results of the implementation of the proposed algorithms. The results show that the quality of the compression rate reduction of about 2 kbps is still satisfactory, and dedicated DSP technology for better speech quality results is a basis for helping vocoder device developers choose the right hardware technology when designing products.

Neurally Optimized Decoder for Low Bitrate Speech Codec

Recently, a conventional neural decoder for speech codec has shown promising performance. However, it typically requires some prior knowledge of decoding such as bit allocation or dequantization scheme, which is not a universal solution for many different kinds of speech codecs. In order to address this limitation, we propose a neurally optimized decoder based on a generative model which can directly reconstruct the speech from the bitstream without a prior knowledge. The proposed decoder mainly consists of two components: 1) a dequantization model to group and dequantize related bits from the bitstream and 2) a generative model to restore the speech conditioned on the output of the dequantization model. Through experiments with mixed excitation linear prediction (MELP), Advanced multi-band excitation (AMBE), and SPEEX at around 2.4 kb/s, it is showed that the proposed model showed better performance in most of the objective and subjective evaluation compared to the conventional speech codecs.

AN EFFICIENT SPEECH GENERATIVE MODEL BASED ON DETERMINISTIC/STOCHASTIC SEPARATION OF SPECTRAL ENVELOPES

The paper presents a speech generative model that provides an efficient way of generating speech waveform from its amplitude spectral envelopes. The model is based on hybrid speech representation that includes deterministic (harmonic) and stochastic (noise) components. The main idea behind the approach originates from the fact that speech signal has a determined spectral structure that is statistically bound with deterministic/stochastic energy distribution in the spectrum. The performance of the model is evaluated using an experimental low-bitrate wide-band speech coder. The quality of reconstructed speech is evaluated using objective and subjective methods. Two objective quality characteristics were calculated: Modified Bark Spectral Distortion (MBSD) and Perceptual Evaluation of Speech Quality (PESQ). Narrow-band and wide-band versions of the proposed solution were compared with MELP (Mixed Excitation Linear Prediction) speech coder and AMR (Adaptive Multi-Rate) speech coder, respectively. The speech base of two female and two male speakers were used for testing. The performed tests show that overall performance of the proposed approach is speaker-dependent and it is better for male voices. Supposedly, this difference indicates the influence of pitch highness on separation accuracy. In that way, using the proposed approach in experimental speech compression system provides decent MBSD values and comparable PESQ values with AMR speech coder at 6,6 kbit/s. Additional subjective listening testsdemonstrate that the implemented coding system retains phonetic content and speaker’s identity. It proves consistency of the proposed approach.

Robust Speech Filter and Voice Encoder Parameter Estimation Using the Phase–Phase Correlator

In recent years, linear prediction voice encoders have become very efficient in terms of computing execution time and channel bandwidth usage while providing, in the absence of impulsive noise, natural sounding synthetic speech signals. This good performance has been achieved via the use of a maximum likelihood parameter estimation of an auto-regressive model of order ten that best fits the speech signal under the assumption that the signal and the noise are Gaussian stochastic processes. However, this method breaks down in the presence of impulse noise, which is common in practice, resulting in harsh or non-intelligible audio signals. In this paper, we propose a robust estimator of correlation, the Phase-Phase correlator that is able to cope with impulsive noise. Utilizing this correlator, we develop a Robust Mixed Excitation Linear Prediction encoder that provides improved audio quality for voiced, unvoiced, and transition speech segments. This is achieved by applying a statistical test to robust Mahalanobis distances for identifying the outliers in the corrupted speech signal, which are then replaced with filtered signals. Simulation results reveal that the proposed estimator of correlator outperforms in variance, bias, and breakdown point compared to three other robust approaches based on the arcsin law, the polarity coincidence correlator, and the median-of-ratio estimator without sacrificing the encoder bandwidth efficiency and the compression gain while remaining compatible with real-time applications. Furthermore, in the presence of impulsive noise, the proposed speech encoder speech subjective quality outperforms the state-of-the-art in terms of mean opinion score.

Design of MELPe-Based Variable-Bit-Rate Speech Coding with Mel Scale Approach Using Low-Order Linear Prediction Filter and Representing Excitation Signal Using Glottal Closure Instants

In this paper, we propose a variable-bit-rate speech codec-based on mixed excitation linear prediction enhanced (MELPe) with an average bit rate of 2 kbps and with a better representation of excitation signal. The order of the prediction filter in MELPe coding architecture is reduced from 10 to 7 without affecting the perceptual quality of the decoded speech by using psychoacoustic Mel scale. An efficient two-split vector quantization is developed with weighted Euclidean distance measure for Mel scale-based linear predictive coding (Mel-LPC), and it requires only 18 bits/frame. The instantaneous pitch or epoch that is vital for many speech processing applications is preserved in this codec by including it in the excitation signal used for reconstructing the voiced speech. The quantization scheme developed for glottal closure instants (GCIs) causes an increase in the bit requirement for voiced frames by 4–25 bits depending on the position of GCIs. To compensate for that, the Mel-LPC order for both silence and unvoiced frames has been brought down to 4 without compromising the perceptual quality of reconstructed speech. The lowered bit budget for unvoiced frame is 41 bits/frame, and for silence, it is 31 bits/frame. Further reduction of 10 bits for silence frame is obtained by reducing the number of transmitted parameters and by tuning the quantization bit requirement for each. For categorizing the speech frames at the entry of the encoder, a neural network-based voiced/unvoiced/silence classification algorithm using five-dimensional feature set is created. The experimental results show that the proposed coding scheme operates at an average bit rate of 2 kbps, which is less than the bit rate of MELPe (2.4 kbps), but with a better perceptual score. In addition to all these, the incorporation of Mel-LPC gives a better performance in the estimation of formants and GCIs.

Pitch and Fourier magnitude based steganography for hiding 2.4 kbps MELP bitstream

In this study, the authors present a new steganographic technique called random least significant bits of pitch and Fourier magnitude steganography (RLPFS). It is based on hiding a secret speech coded by mixed excitation linear prediction (MELP) speech coder in speech bitstream (cover signal), which is also encoded by MELP coder. First, the RLPFS leaks the hidden speech in the following modes: pitch-based steganography, Fourier magnitude-based steganography or both. These modes are selected randomly. Second, during transmission, the stego speech, the mode number, and the number of embedded bits would be transmitted either through a covert channel created in the transmission protocol or through the cover speech. In this work, the authors have dealt with the challenge of embedding a secret speech into a cover speech coded by a very low bit rate speech coder while maintaining a reasonable level of speech quality. They have shown that RLPFS was able to create hidden channels with maximum steganographic bandwidths up to 266.64 bit/s at the cost of a steganographic noise between 0.031 and 0.62 mean opinion score. Also, this study takes into account the security of the parameters, the synchronisation of the receiver to deal with a packet loss during transmission and the resistance of the proposed method against steganalysis.

An extended Levinson-Durbin algorithm and its application in mixed excitation linear prediction

Ten order all-pole model is used in the 2400 bit/second mixed excitation linear prediction to describe human vocal tract. Traditional Levinson-Durbin algorithm is one of the methods to solve the Yule-Walker equations conducted by the ten order linear prediction model. Taking the iteration step of traditional Levinson-Durbin algorithm as 1, an extended algorithm with any positive integer iteration step which is no larger than the order of Teoplitz matrix is proposed. The extended algorithm considers interaction between the adjacent subtracts. A hybrid algorithm of the extended algorithm and traditional algorithm has been applied to solve the 2400 bit/second mixed excitation linear prediction under some conditions. The perceptual evaluation of speech quality mean opinion score of nasal syllable is improved in some degree.

An investigation on the degradation of different features extracted from the compressed American English speech using narrowband and wideband codecs

Speech coding facilitates speech compression without perceptual loss that results in the elimination or deterioration of both speech and speaker specific features used for a wide range of applications like automatic speaker and speech recognition, biometric authentication, prosody evaluations etc. The present work investigates the effect of speech coding in the quality of features which include Mel Frequency Cepstral Coefficients, Gammatone Frequency Cepstral Coefficients, Power-Normalized Cepstral Coefficients, Perceptual Linear Prediction Cepstral Coefficients, Rasta-Perceptual Linear Prediction Cepstral Coefficients, Residue Cepstrum Coefficients and Linear Predictive Coding-derived cepstral coefficients extracted from codec compressed speech. The codecs selected for this study are G.711, G.729, G.722.2, Enhanced Voice Services, Mixed Excitation Linear Prediction and also three codecs based on compressive sensing frame work. The analysis also includes the variation in the quality of extracted features with various bit-rates supported by Enhanced Voice Services, G.722.2 and compressive sensing codecs. The quality analysis of extracted epochs, fundamental frequency and formants estimated from codec compressed speech was also performed here. In the case of various features extracted from the output of selected codecs, the variation introduced by Mixed Excitation Linear Prediction codec is the least due to its unique method for the representation of excitation. In the case of compressive sensing based codecs, there is a drastic improvement in the quality of extracted features with the augmentation of bit rate due to the waveform type coding used in compressive sensing based codecs. For the most popular Code Excited Linear Prediction codec based on Analysis-by-Synthesis coding paradigm, the impact of Linear Predictive Coding order in feature extraction is investigated. There is an improvement in the quality of extracted features with the order of linear prediction and the optimum performance is obtained for Linear Predictive Coding order between 20 and 30, and this varies with gender and statistical characteristics of speech. Even though the basic motive of a codec is to compress single voice source, the performance of codecs in multi speaker environment is also studied, which is the most common environment in majority of the speech processing applications. Here, the multi speaker environment with two speakers is considered and there is an augmentation in the quality of individual speeches with increase in diversity of mixtures that are passed through codecs. The perceptual quality of individual speeches extracted from the codec compressed speech is almost same for both Mixed Excitation Linear Prediction and Enhanced Voice Services codecs but regarding the preservation of features, the Mixed Excitation Linear Prediction codec has shown a superior performance over Enhanced Voice Services codec.

A 600bps Vocoder Algorithm Based on MELP

In order to meet the bandwidth requirements of low-bit-rate speech communication, there is an improvement of standard Mixed Excitation Linear Prediction (MELP) encoder and a 600bps MELP vocoder algorithm with higher quality is proposed. The algorithm forms a super frame by using 5 sub-frames. Joint quantization was carried out to remove redundancy information between intra-frames and inter-frames. We use the method of predictive split vector quantization to quantize the Line Spectral Frequency (LSF) parameters and the other parameters are jointly quantized. Compared to standard 2.4kbps MELP vocoder, the Mean Opinion Score(MOS) of the synthetic speech which is synthesized by the vocoder using the proposed algorithm is 2.54, and the synthetic speech quality is good.

An Improved Frame Loss Concealment Algorithm Based on the Mixed Excitation Linear Prediction

An improved frame loss concealment algorithm based on the Mixed Excitation Linear Prediction (MELP) is presented in this paper. It introduces the Future frame to recover the lost frame and the intermediate frame (U/V frame and V/U frame) to determine the type of lost frame more accurately. Meanwhile, it proposes the Lagrange polynomial approach algorithm and the linear prediction algorithm to recover the parameters of lost frames in different frame types. The PESQ-MOS test shows that the synthetic speech quality has been improved with the algorithm which this paper has proposed.

Research on an Embedded Ultra-Low-Bit-Rate Speech Coding Algorithm

Ultra-low-bit-rate speech coding algorithm was in great demand for many fields such as underwater speech communications. Underwater speech communication for middle-long distance has the characteristics of narrow bandwidth as well as low transmission rate, which makes the underwater speech communication much difficult. Ultra-low-bit-rate speech coding algorithm plays an important role on this occasion. More over, it will be more flexible for the underwater speech communication system if the speech coding algorithm has an embedded structure. The paper introduced the principle of an embedded speech coding algorithm with dual rates at both 300bps and 400bps based on the enhanced mixed excitation linear prediction model. The results show that this embedded ultra-low-bit-rate speech coding algorithm has satisfactory quality under both DRT and MOS test.

Speech Coding Algorithm with Dynamic Weighted Inter-Frame Linear Prediction

A new multi-frame joint quantization algorithm with dynamic weighted inter-frame linear prediction based on mixed excitation linear prediction (MELP) is proposed in this paper. In encoding stage, a super-frame consists of three adjacent single-frames. Fourier magnitudes and aperiodic jitter flag are eliminated. The other parameters are jointly quantized. LSF of the first and third frame are quantized as a 20-dimensional vector. According to the BPVs of super-frame, pitch is quantized with codebooks of dynamic size. In decoding stage, parameters are indexed from corresponding codebook. The LSF of middle frame are predicted from the first and third frame. The weighted factors keep changing in accordance with the BPVs of adjacent five frames. Results show that the reconstruction accuracy of LSF is significantly improved using dynamic weighted inter-frame linear prediction. Meanwhile the coding bit rate is reduced to 0.6 kbps.

Implementation and Design of Underwater Duplex Speech Communication System Based on Vector Hydrophone

This paper realizes 1.2kbps Mixed Excitation Linear Prediction (MELP) speech compression algorithm through multi-frame joint and Vector Quantization technology. In order to adapt to underwater acoustic channel, we apply the Orthogonal Frequency Division Modulation (OFDM) to modulate the source bits, together with synchronization, channel estimation and RS error correcting code technology. The hardware platform of this system relies on TMS320DM642 and AIC23. Moreover, we introduce single vector hydrophone to restrain the local source. The system finished duplex speech signal acquisition and transmission and tank test results prove that the synthesized speech is clear and understandable and it has a stable performance.

Study of underwater speech coding technique based on contact conduction transmitter.

Low bit rate speech coding of 2.4 kbps is actualized by mixed excitation linear prediction algorithm, which meets the requirement of high data rate of underwater speech communication system and the limit of high communication rate of underwater acoustic communication technique. In the process of speech coding, a great deal of speech data is compressed to high speed underwater acoustic communication, and the main characteristics of speaker are remained perfectly. Meanwhile, the capability of avoiding interference is improved obviously by the speech based on contact conduction transmitter as input signal. This underwater speech coding technique and differential OFDM technique are combined and experimented under 434, 1310, and 2000 m in the lake. The real-time transmission of speech signal is presented in the condition of complicated multi-path in the extremely shallow sea. The results show the synthesized speech has well quality of intelligibility and clarity, which satisfies the demand of underwater speech coding.

Vowel Onset Point Detection for Low Bit Rate Coded Speech

In this paper, we propose a method for detecting the vowel onset points (VOPs) for low bit rate coded speech. VOP is the instant at which the onset of the vowel takes place in the speech signal. VOP plays an important role for the applications, such as consonant-vowel (CV) unit recognition and speech rate modification. The proposed VOP detection method is based on the spectral energy present in the glottal closure region of the speech signal. Speech coders considered to carry out this study are Global System for Mobile Communications (GSM) full rate, code-excited linear prediction (CELP), and mixed-excitation linear prediction (MELP). TIMIT database and CV units collected from the broadcast news corpus are used for evaluation. Performance of the proposed method is compared with existing methods, which uses the combination of evidence from the excitation source, spectral peaks energy, and modulation spectrum. The proposed VOP detection method has shown significant improvement in the performance compared to the existing method under clean as well as coded cases. The effectiveness of the proposed VOP detection method is analyzed in CV recognition by using VOP as an anchor point.

A NEW DISTORTION MEASURE FOR PARAMETER QUANTIZATION BASED ON MELP

Parameter quantization is very important for the synthetic speech quality of the vocoder. A new distortion measure for pitch as well as lsf quantization in ultra low bit rate Vocoder, whose parameters for several consecutive frames are grouped into a vector and jointly quantized to obtain high coding efficiency, is proposed based on mixed excitation linear prediction(MELP) vocoder. The product of sum of band pass voicing coefficients and gain parameter is used to denote the weighting factor of pitch as well as lsf parameters of current speech frame in the consecutive frames using weighted squared Euclidean distance measure to search the vector codebook. Comparing with the traditional method for a constant weighting factor by distinguishing Voiced/Unvoiced(UV) pattern of each speech frame, objective test results show that the quantization distortion of pitch is reduced by 3.3% and the mean opinion score (MOS) is increased by almost 0.1(3.5%).

Hidden data transmission in mixed excitation linear prediction coded speech using quantisation index modulation

In this study novel data hiding methods that embed secret data during mixed excitation linear prediction (MELP) coding of the speech signal are proposed. The secret data bits are hidden by using quantisation index modulation (QIM) which is carried out in the multistage vector quantisation (MSVQ) of line spectral frequencies (LSF) parameters. The distortion rates, introduced by the proposed data hiding methods, are compared with that of a previously published dither-like data hiding method by employing tests performed on the speech files selected from NTIMIT database. Weighted Euclidian distances and spectral distortion are calculated as objective distortion quality metrics, whereas perceptual evaluation of speech quality, PESQ P.862, which tries to mimic mean opinion scores, is used to give subjective listening test results. After the calculation of objective and subjective quality metrics, it is determined that the methods with QIM at the third and fourth stages of the MSVQ distort speech only as much as that resulting from a 10 -3 bit error rated (BER) additive white Gaussian noise (AWGN) channel. Later, steganographic strengths of some selected QIM methods are elaborated by the steganalysis methods trained with the computed chaotic features. According to the steganalysis results, methods that apply QIM on the third and fourth indexes of MELP-MSVQ assure both lower distortion and better steganographic imperceptibility.

Bit rate reduction of mixed excitation linear prediction coder by Lempel-Ziv segment quantization

Bit rate reduction of mixed excitation linear prediction coder by Lempel-Ziv segment quantization

Robust Transmission of Multistage Vector Quantized Sources Over Noisy Communication Channels—Applications to MELP Speech Codec

Joint source-channel coding is an effective approach for the design of bandwidth efficient and error resilient communication systems with manageable complexity. An interesting research direction within this framework is the design of source decoders that exploit the residual redundancy for effective signal reconstruction at the receiver. Such source decoders are expected to replace the traditionally heuristic error concealment units that are elements of most multimedia communication systems. In this paper, we consider the reconstruction of signals encoded with a multistage vector quantizer (MSVQ) and transmitted over a noisy communications channel. The MSVQ maintains a moderate complexity and, due to its successive refinement feature, is a suitable choice for the design of layered (progressive) source codes. An approximate minimum mean squared error source decoder for MSVQ is presented, and its application to the reconstruction of the linear predictive coefficient (LPC) parameters in mixed excitation linear prediction (MELP) speech codec is analyzed. MELP is a low-rate standard speech codec suitable for bandwidth-limited communications and wireless applications. Numerical results demonstrate the effectiveness of the proposed schemes

An improved 2.4kb/s Mixed Excitation Linear Prediction vocoder

This letter presents two improvements on 2.4 kb/s Mixed-Excitation Linear Prediction (MELP) vocoder. The one is a new parameter R edzc named energy to differential zero-crossing rate which is used in adaptation of V/UV decision of transitional segments and low energy level speech segments. The other is a multi-path searching method for Multi-Stage Vector Quantization (MSVQ) of line spectral frequency. Subjective tests show that the intelligiblity and naturallity of improved MELP vocoder are preferable to those of the original one.