Enhanced waveform interpolative coding at low bit-rate

Gottesman, O.; Gersho, A.

doi:10.1109/89.966082

Cited by 19 publications

(6 citation statements)

References 28 publications

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“…In any case, their most outstanding utilization is bit rate saving in a systems administration medium, for example, a cell phone cell or a parcel network association with permit more clients. Then again, to guarantee more excellent playback, a highgoal coder or a more detailed coding framework may be required [107]. Truth be told, the accessibility of ever more extensive band associations and bigger limit media has made some view discourse encryption as unnecessary, yet the developing populace of transmitters and the undeniably more extravagant substance have taken up the "data transfer capacity" made available by the approach of broadband administrations.…”

Section: Low Bit Rate Speech Codingmentioning

confidence: 99%

Paralinguistic Speech Processing: An Overview

Abdullah

Ameen

Ahmed

et al. 2021

AJRCoS

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Clients can adequately control PCs and create reports by speaking with the guide of innovation, discourse acknowledgment empowers records to be delivered all the more effectively in light of the fact that the program normally produces words as fast as they expressed, which is typically a lot faster than a human can compose. Discourse acknowledgment is an innovation that consequently finds the words and expressions that best match the contribution of human discourse. The most normal use of discourse acknowledgment is correspondence, where discourse acknowledgment can be utilized to create letters/messages and different reports. Point of discourse handling: - to comprehend discourse as a mechanism of correspondence, to reflect discourse for transmission and propagation; - to inspect discourse for robotized data discovery and extraction-to find some physiological highlights of the speaker. In discourse combination, there are two significant capacities. The first is the interpretation of voice to message. The second is for the content to be converted into human voice.

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Section: Low Bit Rate Speech Codingmentioning

confidence: 99%

Paralinguistic Speech Processing: An Overview

Abdullah

Ameen

Ahmed

et al. 2021

AJRCoS

View full text Add to dashboard Cite

show abstract

“…In recent years, the speech coding rate become lower and lower. Speech coding algorithms with rate below 2.4kbps, which are also called ultra-low-bit-rate speech coding algorithms, become one of the most important research topics [1][2][3][4][5][6]. And many speech coding models were proposed, such as mixed excitation linear prediction (MELP) model, multi-band excitation (MBE) model, sinusoidal transform coding (STC) and waveform interpolation (WI).…”

Section: Introductionmentioning

confidence: 99%

A Pitch Detection Algorithm for Ultra-low-bit-rate Vocoder

Li¹,

Jiang²,

Hao³

et al. 2012

Proceedings of the 2nd International Conference on Computer Application and System Modeling

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Abstract-Pitch is one of the most important parameters to describe the speech characteristics. The paper proposed a new pitch detection algorithm for ultra-low-bit-rate vocoder based on dynamic programming as well as frequency-time domain analysis to eliminate the multi-half pitch errors. The algorithm detected the candidate pitches based on auto correlation function firstly and then utilized the dynamic programming and frequency-time domain analysis to get the final pitch. Simulation result showed that the algorithm had a better performance and could eliminate the multi-half pitch errors efficiently.

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“…In [11] and [12], the phase residual, the difference between the phase of the current frame, and its prediction from the previous frame is quantized. Vector quantization of phases was proposed in [13] for the quantization of the harmonic phases of the slowly evolving waveform (SEW) in the context of waveform interpolation (WI) coders. An important contribution of the latter work is the introduction of a distortion measure that takes into account the modulo-behavior of phases and the derivation of the corresponding k-means algorithm for codebook training.…”

Section: Introductionmentioning

confidence: 99%

Wrapped Gaussian Mixture Models for Modeling and High-Rate Quantization of Phase Data of Speech

Agiomyrgiannakis

Stylianou

2009

IEEE Trans. Audio Speech Lang. Process.

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Abstract-The harmonic representation of speech signals has found many applications in speech processing. This paper presents a novel statistical approach to model the behavior of harmonic phases. Phase information is decomposed into three parts: a minimum phase part, a translation term, and a residual term referred to as dispersion phase. Dispersion phases are modeled by wrapped Gaussian mixture models (WGMMs) using an expectation-maximization algorithm suitable for circular vector data. A multivariate WGMM-based phase quantizer is then proposed and constructed using novel scalar quantizers for circular random variables. The proposed phase modeling and quantization scheme is evaluated in the context of a narrowband harmonic representation of speech. Results indicate that it is possible to construct a variable-rate harmonic codec that is equivalent to iLBC at approximately 13 kbps.Index Terms-Circular statistics, , phase quantization, sinusoidal models, speech analysis, speech coding, voice-over-IP, wrapped Gaussian mixture models (WGMMs).

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Enhanced waveform interpolative coding at low bit-rate

Cited by 19 publications

References 28 publications

Paralinguistic Speech Processing: An Overview

Paralinguistic Speech Processing: An Overview

A Pitch Detection Algorithm for Ultra-low-bit-rate Vocoder

Wrapped Gaussian Mixture Models for Modeling and High-Rate Quantization of Phase Data of Speech

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