Progress in LPC-based frequency-domain audio coding

Moriya, Takehiro; Sugiura, Ryo; Kamamoto, Yutaka; Kameoka, Hirokazu; Harada, Noboru

doi:10.1017/atsip.2016.11

Cited by 7 publications

(2 citation statements)

References 51 publications

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“…However, their recording conditions usually do not satisfy the recommendations for voice research [24], [25]. Moreover, they are usually using lossy audio digital compression [26]. The proposed method is useful for assessing degradations introduced by these non-ideal recording and coding conditions by decomposing the response into the linear time-invariant responses and other nonlinear and time-varying responses.…”

Section: Discussionmentioning

confidence: 99%

Simultaneous measurement of time-invariant linear and nonlinear, and random and extra responses using frequency domain variant of velvet noise

Kawahara,

Sakakibara,

Mizumachi

et al. 2020

Preprint

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We introduce a new acoustic measurement method that can measure the linear time-invariant response, the nonlinear time-invariant response, and random and time-varying responses simultaneously. The method uses a set of orthogonal sequences made from a set of unit FVNs (Frequency domain variant of Velvet Noise), a new member of the TSP (Time Stretched Pulse). FVN has a unique feature that other TSP members do not. It is a high degree of design freedom that makes the proposed method possible without introducing extra equipment. We introduce two useful cases using two and four orthogonal sequences and illustrates their use using simulations and acoustic measurement examples. We developed an interactive and realtime acoustic analysis tool based on the proposed method. We made it available in an open-source repository. The proposed response analysis method is general and applies to other fields, such as auditory-feedback research and assessment of sound recording and coding.

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Section: Discussionmentioning

confidence: 99%

Simultaneous measurement of time-invariant linear and nonlinear, and random and extra responses using frequency domain variant of velvet noise

Kawahara,

Sakakibara,

Mizumachi

et al. 2020

Preprint

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“…In both conventional vocoders and waveform coders, linear predictive coding (LPC) [7], an all-pole linear filter, serves a critical component, as it can efficiently model power spectrum with only a few coefficients through Levinson-Durbin algorithm [6]. For vocoders, the LPC residual is then modeled as a synthetic excitation signal with a pitch pulse train or white noise component [8]. On the other hand, for waveform coders, such as Opus [9], Speex [10] and AMR-WB [11], the residual is directly compressed to the desired bitrate before being synthesized to the decoded signal.…”

Section: Introductionmentioning

confidence: 99%

Efficient and Scalable Neural Residual Waveform Coding with Collaborative Quantization

Zhen

Lee

Sung

et al. 2020

ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

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Scalability and efficiency are desired in neural speech codecs, which supports a wide range of bitrates for applications on various devices. We propose a collaborative quantization (CQ) scheme to jointly learn the codebook of LPC coefficients and the corresponding residuals. CQ does not simply shoehorn LPC to a neural network, but bridges the computational capacity of advanced neural network models and traditional, yet efficient and domain-specific digital signal processing methods in an integrated manner. We demonstrate that CQ achieves much higher quality than its predecessor at 9 kbps with even lower model complexity. We also show that CQ can scale up to 24 kbps where it outperforms AMR-WB and Opus. As a neural waveform codec, CQ models are with less than 1 million parameters, significantly less than many other generative models.

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Speech Enhancement and Encoding using SS-VAD and LPC

Nayana

et al. 2019

2019 4th International Conference on Electrical, Electronics, Communication, Computer Technologies and Optimization Techniques

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Progress in LPC-based frequency-domain audio coding

Abstract: Progress in LPC-

Cited by 7 publications

References 51 publications

Simultaneous measurement of time-invariant linear and nonlinear, and random and extra responses using frequency domain variant of velvet noise

Simultaneous measurement of time-invariant linear and nonlinear, and random and extra responses using frequency domain variant of velvet noise

Efficient and Scalable Neural Residual Waveform Coding with Collaborative Quantization

Speech Enhancement and Encoding using SS-VAD and LPC

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