Abstract
At the threshold of understanding speech in noisy environments, the neural exploitation of interaural differences constitutes a significant margin of intelligibility. Mimicking spatial hearing for improving speech intelligibility in hearing aids and robotics has been demonstrated by compelling results. This chapter reviews binaural speech processors and highlights approaches for their optimal application. Binaural algorithms of speech enhancement draw on the assumption that the target and the noise signal strike a head-mounted processor from different directions and cause distinctive interaural parameters. This assumption is, however, often violated in degraded acoustics. In order to study this degradation, the chapter starts with an examination of binaural statistics in different noise conditions. Subsequently, standard binaural speech processors are studied that use different waveform features, namely, the binaural coherence of the fine-structure, the binaural differences of the fine-structure and the binaural differences of the envelope. As a means to cater to a fair comparison, each algorithm underwent a stochastic optimization of the algorithmic parameters in a set of prototypical speech-in-noise scenes, whereby an instrumental measure of speech intelligibility served as the objective function. Furthermore, the binaural speech processors are applied at the output of commercially-available hearing aids that feature superdirective beamformers with different directivity modes. In this way, the SNR-gain that adds to the pre-processing of the beamformer is assessed. For deriving filter gains from binaural statistics, part three of this chapter describes histogram-based methods and parametric approaches for the binaural fine-structure algorithm, and compares these in a realistic environment with reverberation and additive noise. Part three can also be read as a hands-on description, thereby addressing students and engineers, who are striving for an ad-hoc implementation of a binaural system for speech enhancement.
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Notes
- 1.
For a particular direction of sound incidence, the interaural transfer function is defined as the quotient of the corresponding head-related transfer functions at each ear. There is also a running interaural amplitude-modulation transfer function for a particular sound direction, which is equivalent to the quotient of the corresponding amplitude-modulation transfer functions of each ear. While the former is rooted in binaural differences of the fine-structure of the waveform, the latter is caused by interaural differences of the envelope. Both types of transfer functions are approximately independent of each other.
- 2.
Disjointness between two signals in the time-frequency domain, for instance, the signal \(\delta _{j}(d, m)\) and the signal \(\delta _{j^{\prime }}(d, m)\) can be expressed as \(\delta _{j}(d, m)\delta _{j^{\prime }}(d, m) \approx 0\), \( \forall j^{\prime } \not = j\), where \(d\) and \(m\) denote the frequency and time index, respectively.
- 3.
The same recording chain as well as the same source-receiver distance were applied during the HRTF measurements in the anechoic chamber of the Bochum institute.
- 4.
- 5.
The I3 has originally been developed to predict the effects of additive noise, peak clipping and center clipping on speech intelligibility [20].
- 6.
Throughout this chapter, the target source and the interferers were arranged in the horizontal plane.
- 7.
The hearing-aid program low of the hearing glasses provides a benefit of 4.4Â dB as assessed with the directivity-index method of the ANSI S3.35-2005 standard [4]. In the mode high the hearing aid offers an improvement of the directivity index of 7.2Â dB.
- 8.
The term coherent-interference condition was used here to describe an interfering sound source under an-echoic conditions.
- 9.
In order to provide for an instrumental measure of absolute perceptual speech intelligibility, a perceptual intelligibility test with the applied speech material as well as a subsequent fitting of the instrumental results to the perceptual recognition scores with a logistic function need to be executed. Therefore, un-fitted instrumental measures merely quantify trends.
- 10.
The current section is an excerpt from the diploma thesis of Ch. Luther, Speech intelligibility enhancement based on multivariate models of binaural interaction, Ruhr-University Bochum, 2012. Contact the author to obtain a copy.
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Acknowledgments
The authors gratefully acknowledge their indebtedness to two anonymous reviewers for helpful advice. Part of this work has been supported by the Dutch Technology Foundation STW-project # DTF.7459.
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Schlesinger, A., Luther, C. (2013). Optimization of Binaural Algorithms for Maximum Predicted Speech Intelligibility. In: Blauert, J. (eds) The Technology of Binaural Listening. Modern Acoustics and Signal Processing. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-37762-4_11
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