A Comparison of Orthogonal Transformations for Digital Speech Processing

Campanella, S. J.; Robinson, Guner S.

doi:10.1109/tcom.1971.1090777

Cited by 44 publications

(4 citation statements)

References 7 publications

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“…A comparison of the DFT, the WHT and the KLT for full-band speech coding has been carried out by Campanella and Robinson [80] based on the improvement of signal-to-quantizing-noise over PCM. …”

Section: Transform Codingmentioning

confidence: 99%

Hybrid frequency-domain coding of speech signals

Foo

Turner

1983

IEE Proc. F Commun. Radar Signal Process. UK

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A new method of coding speech signals is introduced and its application to the low-bit-rate transmission of speech is examined. The new method, which is referred to as hybrid frequency-domain coding (HFDC), is based on a combination of sub-band coding and transform coding techniques and thus involves block coding.In one version of the HFDC scheme, a fixed data rate is used. In this version, blocks of speech signal are coded using a fixed number of bits. The technique is of relatively low complexity and results of subjective tests indicate that the quality of speech produced by the technique at 7.2 kbit/s is comparable with that produced by 19 kbit/s continuously variable slope delta modulation (CVSD); and that at 9.6 kbit/s, it is comparable with 23 kbit/s CVSD.In a further application of the HFDC scheme, a variable bit rate technique is used which takes account of the nonstationary nature of speech. Block coding is again used but. the number of bits allocated is made to depend on the characteristics of the block. Subjective tests have shown that. improved speech quality can be obtained at the expense of slightly increased end-to-end delay.Quadrature mirror filters are important in sub-band coding and a new method of designing these filters is described. The effects of finite-word-length on the performance of systems using quadrature mirror filters are considered and formulae are derived relating to the bounds and variances of the errors due to analog-to-digital conversion; quantization of the filter coefficients; roundoff in arithmetic computations and the quantization associated with compression encoding. The results obtained from extensive simulations are shown to be in excellent agreement with the theoretically derived values.Various other issues relating to the design of the HFDC scheme are considered. These include the analysis of errors resulting from the use of the block-floating-point fast Walsh-Hadamard transform, and the automatic classification of speech into voiced, unvoiced and silent intervals. Last but not least, I would like to express my thanks to Dr.Tay Eng Soon for his support and encouragement; and to the Ministry of Defence for granting the DSO scholarship and the paid study leave. 5

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Section: Transform Codingmentioning

confidence: 99%

Hybrid frequency-domain coding of speech signals

Foo

Turner

1983

IEE Proc. F Commun. Radar Signal Process. UK

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“…Our approach is similar but more systematic and with more concise notation than those of Kahaner [24] and Drubin [25]. The recursive use of the formulae (10) and (11) gives the number of required operations. In the case of N r" we can solve these recursive equations: This is the case of FFT of radix r.…”

Section: Recursive Generative Rules We Shall Present Three Basic Andmentioning

confidence: 99%

“…The Haar transform, although closely related to the Walsh-Hadamard transform [6] and potentially of interest [7], has received much less attention. These transforms have been used successfully for signal filtering [8], pattern classification [4], [9], speech signal encoding [10] and above all for picture encoding [11], [12], [13]. An overview of transforms can be found in [37] and [38].…”

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confidence: 99%

A Unified Treatment of Discrete Fast Unitary Transforms

Fino¹,

Algazi²

1977

SIAM J. Comput.

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A set of recursive rules which generate unitary transforms with a fast algorithm (FUT) are presented. For each rule, simple relations give the number of elementary operations required by the fast algorithm. The common Fourier, Walsh-Hadamard (W-H), Haar, and Slant transforms are expressed with these rules. The framework developed allows the introduction of generalized transforms which include all common.transforms in a large class of "identical computation transforms". A systematic and unified view is provided for unitary transforms which have appeared in the literature. This approach leads to a number of new transforms of potential interest. Generalization to complex and multidimensional unitary transforms is considered and some structural relations between transforms are established. Key words, discrete transforms, fast algorithms, fast Fourier transforms, fast generalized transforms, generalized Kronecker product, Haar transform, identical computation transforms, slant transform, unitary transforms and matrices, Walsh-Hadamard transform *

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“…Many compact signal representation techniques such as subband coding have been developed to improve storage and processing efficiency [1]. The processing of these compacted signals offers computational advantages and has been widely used for data compression [2], noise reduction [3], and speech and image coding [4], [5]. This work focuses on the compact representation of speech signals measured by spherical microphone arrays.…”

Section: Introductionmentioning

confidence: 99%

Signal Compaction Using Polynomial EVD for Spherical Array Processing With Applications

Neo,

Evers,

Weiss

et al. 2023

IEEE/ACM Trans. Audio Speech Lang. Process.

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Multi-channel signals captured by spatially separated sensors often contain a high level of data redundancy. A compact signal representation enables more efficient storage and processing, which has been exploited for data compression, noise reduction, and speech and image coding. This paper focuses on the compact representation of speech signals acquired by spherical microphone arrays. A polynomial matrix eigenvalue decomposition (PEVD) can spatially decorrelate signals over a range of time lags and is known to achieve optimum multichannel data compaction. However, the complexity of PEVD algorithms scales at best cubically with the number of channel signals, e.g., the number of microphones comprised in a spherical array used for processing. In contrast, the spherical harmonic transform (SHT) provides a compact spatial representation of the 3-dimensional sound field measured by spherical microphone arrays, referred to as eigenbeam signals, at a cost that rises only quadratically with the number of microphones. Yet, the SHT's spatially orthogonal basis functions cannot completely decorrelate sound field components over a range of time lags. In this work, we propose to exploit the compact representation offered by the SHT to reduce the number of channels used for subsequent PEVD processing. In the proposed framework for signal representation, we show that the diagonality factor improves by up to 7 dB over the microphone signal representation with a significantly lower computation cost. Moreover, when applying this framework to speech enhancement and source separation, the proposed method improves metrics known as short-time objective intelligibility (STOI) and source-to-distortion ratio (SDR) by up to 0.2 and 20 dB, respectively.

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A Comparison of Orthogonal Transformations for Digital Speech Processing

Cited by 44 publications

References 7 publications

Hybrid frequency-domain coding of speech signals

Hybrid frequency-domain coding of speech signals

A Unified Treatment of Discrete Fast Unitary Transforms

Signal Compaction Using Polynomial EVD for Spherical Array Processing With Applications

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