In this paper, we evaluate the performance of several objective measures in terms of predicting the quality of noisy speech enhanced by noise suppression algorithms. The objective measures considered a wide range of distortions introduced by four types of real-world noise at two signal-to-noise ratio levels by four classes of speech enhancement algorithms: spectral subtractive, subspace, statistical-model based, and Wiener algorithms. The subjective quality ratings were obtained using the ITU-T P.835 methodology designed to evaluate the quality of enhanced speech along three dimensions: signal distortion, noise distortion, and overall quality. This paper reports on the evaluation of correlations of several objective measures with these three subjective rating scales. Several new composite objective measures are also proposed by combining the individual objective measures using nonparametric and parametric regression analysis techniques.

Evaluation of Objective Quality Measures for Speech Enhancement

Existing speech enhancement algorithms can improve speech quality but not speech intelligibility, and the reasons for that are unclear. In the present paper, we present a theoretical framework that can be used to analyze potential factors that can influence the intelligibility of processed speech. More specifically, this framework focuses on the fine-grain analysis of the distortions introduced by speech enhancement algorithms. It is hypothesized that if these distortions are properly controlled, then large gains in intelligibility can be achieved. To test this hypothesis, intelligibility tests are conducted with human listeners in which we present processed speech with controlled speech distortions. The aim of these tests is to assess the perceptual effect of the various distortions that can be introduced by speech enhancement algorithms on speech intelligibility. Results with three different enhancement algorithms indicated that certain distortions are more detrimental to speech intelligibility degradation than others. When these distortions were properly controlled, however, large gains in intelligibility were obtained by human listeners, even by spectral-subtractive algorithms which are known to degrade speech quality and intelligibility.

/pdf/reasons-why-current-speech-enhancement-algorithms-do-not-d6joni8z73.pdf

Reasons why Current Speech-Enhancement Algorithms do not Improve Speech Intelligibility and Suggested Solutions

Speech coding

Under noise-free conditions, the quality of reverberant speech is dependent on two distinct perceptual components: coloration and long-term reverberation. They correspond to two physical variables: signal-to-reverberant energy ratio (SRR) and reverberation time, respectively. Inspired by this observation, we propose a two-stage reverberant speech enhancement algorithm using one microphone. In the first stage, an inverse filter is estimated to reduce coloration effects or increase SRR. The second stage employs spectral subtraction to minimize the influence of long-term reverberation. The proposed algorithm significantly improves the quality of reverberant speech. A comparison with a recent enhancement algorithm is made on a corpus of speech utterances in a number of reverberant conditions, and the results show that our algorithm performs substantially better.

/pdf/a-two-stage-algorithm-for-one-microphone-reverberant-speech-3rj4xs0fr9.pdf

A two-stage algorithm for one-microphone reverberant speech enhancement

The enhancement of speech which is corrupted by noise is commonly performed in the short-time discrete Fourier transform domain. In case only a single microphone signal is available, typically only the spectral amplitude is modified. However, it has recently been shown that an improved spectral phase can as well be utilized for speech enhancement, e.g., for phase-sensitive amplitude estimation. In this paper, we therefore present a method to reconstruct the spectral phase of voiced speech from only the fundamental frequency and the noisy observation. The importance of the spectral phase is highlighted and we elaborate on the reason why noise reduction can be achieved by modifications of the spectral phase. We show that, when the noisy phase is enhanced using the proposed phase reconstruction, instrumental measures predict an increase of speech quality over a range of signal to noise ratios, even without explicit amplitude enhancement.

STFT phase reconstruction in voiced speech for an improved single-channel speech enhancement

This paper presents the results of a pilot study comparing four different speech waveform coding techniques of varying complexity. Coder transmission rates of 24, 16, and 9.6 Kb/s were used in the experiment. Subjective ratings and objective measurements of quality are obtained and compared. A number of conclusions are drawn concerning the quality and complexity, of different coding techniques. By comparing the objective measurements to the subjective ratings a number of conclusions are also drawn concerning the strengths and weaknesses of various (objective) quality measures of speech waveform coders.

A study of complexity and quality of speech waveform coders

An experiment has been performed to study the perceptual characteristics of speech processed by ADPCM. We created 18 three-bit and four-bit coders spanning a wide range of quantizer adaptation parameters. Subjects judged the difference between each pair of coders and rated the quality of each coder individually. The difference data reveal three important perceptual dimensions (overall clarity, signal vs. background distortion, muffled vs. hoarse) which are related to various objective measures of coder performance. Overall subjective quality is well predicted by segmental SNR and even better by a linear combination of measures of granular distortion and overload distortion.

Perceptual and objective evaluation of speech processed by adaptive differential PCM

An experiment has been performed to study the perceptual characteristics of speech processed by adaptive differential PCM. We created 18 three-bit and four-bit coders spanning a wide range of quantizer adaptation parameters. Subjects judged differences between coders and rated the quality of each coder individually. The difference data reveal three important perceptual characteristics: overall clarity, signal vs. background degradation, and rough vs. smooth impairment. These characteristics are strongly correlated with coder design parameters and objective performance measures. Overall subjective quality is well predicted by segmental signal-to-noise ratio and even better by a linear combination of measures of granular distortion and overload distortion.

http://ieeexplore.ieee.org/iel7/6731005/6771588/06771604.pdf

Perceptual and objective evaluation of speech processed by adaptive differential pcm

Subjective ratings were obtained for four different speech waveform coders of varying complexity at each of three bit rates (24, 16, and 9.6 kb/s). atc (adaptive transform coding) is rated the highest and adpcm-f (adaptive differential pcm with a fixed predictor) the lowest, regardless of bit rate. Although there is large variability in the ratings due to different talkers and listeners, sbc (sub-band coding) is rated higher than adpcm-f and about equal to adpcm-v (adaptive differential pcm with a variable predictor) for most talkers and listeners. A weighted combination of two objective measures, one accounting for noise and the other for bandwidth effects, appears promising as a predictor of the subjective quality ratings.

https://ieeexplore.ieee.org/iel7/6731005/6771421/06771427.pdf

A comparison of the performance of four low-bit-rate speech waveform coders

The spectrum of additive noise was systematically varied according to three variables: correspondance between the noise and speech spectrum (4 levels), equal weighting or weighting according to the width of the Articulation Index bands, SNR of the output signal (2 levels). All combinations of these 16 noise conditions were added to high quality speech sampled at 8kHz, and presented to listeners for judgment. Difference judgments were analyzed by a multidimensional scaling procedure to gain information about the number and nature of the important subjective variables. Overall quality ratings were obtained as a measure of the improvement in perceived quality due to the spectral shaping of the additive noise. Several objective measures were also tested for their sensitivity in predicting the overall quality ratings.

The perception of spectrally shaped additive noise in speech

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