An algorithm is presented for the estimation of the fundamental frequency (F0) of speech or musical sounds. It is based on the well-known autocorrelation method with a number of modifications that combine to prevent errors. The algorithm has several desirable features. Error rates are about three times lower than the best competing methods, as evaluated over a database of speech recorded together with a laryngograph signal. There is no upper limit on the frequency search range, so the algorithm is suited for high-pitched voices and music. The algorithm is relatively simple and may be implemented efficiently and with low latency, and it involves few parameters that must be tuned. It is based on a signal model (periodic signal) that may be extended in several ways to handle various forms of aperiodicity that occur in particular applications. Finally, interesting parallels may be drawn with models of auditory processing.

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YIN, a fundamental frequency estimator for speech and music

In the development process of noise-reduction algorithms, an objective machine-driven intelligibility measure which shows high correlation with speech intelligibility is of great interest. Besides reducing time and costs compared to real listening experiments, an objective intelligibility measure could also help provide answers on how to improve the intelligibility of noisy unprocessed speech. In this paper, a short-time objective intelligibility measure (STOI) is presented, which shows high correlation with the intelligibility of noisy and time-frequency weighted noisy speech (e.g., resulting from noise reduction) of three different listening experiments. In general, STOI showed better correlation with speech intelligibility compared to five other reference objective intelligibility models. In contrast to other conventional intelligibility models which tend to rely on global statistics across entire sentences, STOI is based on shorter time segments (386 ms). Experiments indeed show that it is beneficial to take segment lengths of this order into account. In addition, a free Matlab implementation is provided.

An Algorithm for Intelligibility Prediction of Time–Frequency Weighted Noisy Speech

福祉関連職におけるMaslach Burnout Inventoryの因子構造の比較

(NOTE: Each chapter begins with an introduction and concludes with a Summary, Exercises and Bibliography.) 1. Introduction. Discrete-Time Speech Signal Processing. The Speech Communication Pathway. Analysis/Synthesis Based on Speech Production and Perception. Applications. Outline of Book. 2. A Discrete-Time Signal Processing Framework. Discrete-Time Signals. Discrete-Time Systems. Discrete-Time Fourier Transform. Uncertainty Principle. z-Transform. LTI Systems in the Frequency Domain. Properties of LTI Systems. Time-Varying Systems. Discrete-Fourier Transform. Conversion of Continuous Signals and Systems to Discrete Time. 3. Production and Classification of Speech Sounds. Anatomy and Physiology of Speech Production. Spectrographic Analysis of Speech. Categorization of Speech Sounds. Prosody: The Melody of Speech. Speech Perception. 4. Acoustics of Speech Production. Physics of Sound. Uniform Tube Model. A Discrete-Time Model Based on Tube Concatenation. Vocal Fold/Vocal Tract Interaction. 5. Analysis and Synthesis of Pole-Zero Speech Models. Time-Dependent Processing. All-Pole Modeling of Deterministic Signals. Linear Prediction Analysis of Stochastic Speech Sounds. Criterion of "Goodness". Synthesis Based on All-Pole Modeling. Pole-Zero Estimation. Decomposition of the Glottal Flow Derivative. Appendix 5.A: Properties of Stochastic Processes. Random Processes. Ensemble Averages. Stationary Random Process. Time Averages. Power Density Spectrum. Appendix 5.B: Derivation of the Lattice Filter in Linear Prediction Analysis. 6. Homomorphic Signal Processing. Concept. Homomorphic Systems for Convolution. Complex Cepstrum of Speech-Like Sequences. Spectral Root Homomorphic Filtering. Short-Time Homomorphic Analysis of Periodic Sequences. Short-Time Speech Analysis. Analysis/Synthesis Structures. Contrasting Linear Prediction and Homomorphic Filtering. 7. Short-Time Fourier Transform Analysis and Synthesis. Short-Time Analysis. Short-Time Synthesis. Short-Time Fourier Transform Magnitude. Signal Estimation from the Modified STFT or STFTM. Time-Scale Modification and Enhancement of Speech. Appendix 7.A: FBS Method with Multiplicative Modification. 8. Filter-Bank Analysis/Synthesis. Revisiting the FBS Method. Phase Vocoder. Phase Coherence in the Phase Vocoder. Constant-Q Analysis/Synthesis. Auditory Modeling. 9. Sinusoidal Analysis/Synthesis. Sinusoidal Speech Model. Estimation of Sinewave Parameters. Synthesis. Source/Filter Phase Model. Additive Deterministic-Stochastic Model. Appendix 9.A: Derivation of the Sinewave Model. Appendix 9.B: Derivation of Optimal Cubic Phase Parameters. 10. Frequency-Domain Pitch Estimation. A Correlation-Based Pitch Estimator. Pitch Estimation Based on a "Comb Filter<170. Pitch Estimation Based on a Harmonic Sinewave Model. Glottal Pulse Onset Estimation. Multi-Band Pitch and Voicing Estimation. 11. Nonlinear Measurement and Modeling Techniques. The STFT and Wavelet Transform Revisited. Bilinear Time-Frequency Distributions. Aeroacoustic Flow in the Vocal Tract. Instantaneous Teager Energy Operator. 12. Speech Coding. Statistical Models of Speech. Scaler Quantization. Vector Quantization (VQ). Frequency-Domain Coding. Model-Based Coding. LPC Residual Coding. 13. Speech Enhancement. Introduction. Preliminaries. Wiener Filtering. Model-Based Processing. Enhancement Based on Auditory Masking. Appendix 13.A: Stochastic-Theoretic parameter Estimation. 14. Speaker Recognition. Introduction. Spectral Features for Speaker Recognition. Speaker Recognition Algorithms. Non-Spectral Features in Speaker Recognition. Signal Enhancement for the Mismatched Condition. Speaker Recognition from Coded Speech. Appendix 14.A: Expectation-Maximization (EM) Estimation. Glossary.Speech Signal Processing.Units.Databases.Index.About the Author.

Discrete-Time Speech Signal Processing: Principles and Practice

Phase patterns of neuronal responses reliably discriminate speech in human auditory cortex.

The aim of this study is to gain more insight in the assessment of noise in open-plan study environments and to reveal correlations between noise disturbance experienced by students and the noise sources they perceive, the tasks they perform and the acoustic parameters of the open-plan study environment they work in. Data were collected in five open-plan study environments at universities in the Netherlands. A questionnaire was used to investigate student tasks, perceived sound sources and their perceived disturbance, and sound measurements were performed to determine the room acoustic parameters. This study shows that 38% of the surveyed students are disturbed by background noise in an open-plan study environment. Students are mostly disturbed by speech when performing complex cognitive tasks like studying for an exam, reading and writing. Significant but weak correlations were found between the room acoustic parameters and noise disturbance of students. Practitioner Summary: A field study was conducted to gain more insight in the assessment of noise in open-plan study environments at universities in the Netherlands. More than one third of the students was disturbed by noise. An interaction effect was found for task type, source type and room acoustic parameters.

Noise disturbance in open-plan study environments: a field study on noise sources, student tasks and room acoustic parameters.

This paper presents an empirical method for assessing music similarity on a set of stimuli using triadic comparisons in a balanced incomplete block design. We first evaluated the consistency of subjects in their rankings and then the concordance across subjects. The concordance was also evaluated for different subject populations to assess the influence of experience of the subject with the musical material. We finally analysed subjects’ ranking by the means of multidimensional scaling. Similarity judgments were found to be rather concordant across subjects. Significant differences between musicians and non-musicians and between subjects being familiar or non-familiar with the music were found for a small number of cases. Multidimensional scaling reveals a proximity of songs belonging to the same genre, congruent with the idea of genre being a perceptual dimension in subjects’ similarity ranking.

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Perceptual evaluation of music similarity.

In our natural environment, we simultaneously receive information through various sensory modalities. The properties of these stimuli are coupled by physical laws, so that, e.g., auditory and visual stimuli caused by the same even have a fixed temporal relation when reaching the observer. In speech, for example, visible lip movements and audible utterances occur in close synchrony which contributes to the improvement of speech intelligibility under adverse acoustic conditions. Research into multi- sensory perception is currently being performed in a great variety of experimental contexts. This paper attempts to give an overview of the typical research areas dealing with audio-visual interaction and integration, bridging the range from cognitive psychology to applied research for multimedia applications. Issues of interest are the sensitivity to asynchrony between audio and video signals, the interaction between audio-visual stimuli with discrepant spatial and temporal rate information, crossmodal effects in attention, audio-visual interactions in speech perception and the combined perceived quality of audio-visual stimuli.

Auditory-visual interaction : From fundamental research in cognitive psychology to (possible) applications

Two experiments are reported in this study. In the first experiment the masking effect of five different types of narrow‐band maskers was compared. The masker was either a tone, a narrow‐band Gaussian noise, or a multiplication noise obtained by multiplying a sinusoid with a low‐pass Gaussian noise. The noise maskers had a bandwidth of either 20 or 100 Hz. In all cases the masker had a center frequency of 1.3 kHz and a duration of 500 ms. Five‐point growth‐of‐masking functions were measured using a 2‐kHz tonal target with a duration of 400 ms, temporally centered in the masker. Six subjects participated in the experiment. Although considerable intersubject differences were observed, the data of all subjects showed several common trends. First, the tonal maskers produced more masking than the noise maskers. Second, Gaussian noise maskers produced more masking than multiplication noise maskers of the same bandwidth. Finally, 100‐Hz‐wide noise maskers produced more masking than 20‐Hz‐wide maskers of the same type. Differences in masked thresholds between the various masker types generally increased with masker level, and exceeded 25 dB in some conditions. The results are discussed in terms of masker envelope fluctuations. In the second experiment the masking effect was investigated for a bandpass noise at 1.3 kHz, with regular zero crossings, but with the envelope characteristics of a 100‐Hz‐wide Gaussian noise. Five‐point growth‐of‐masking functions were measured using a tonal target of 2 kHz. Masked thresholds produced by this hybrid masker were not significantly different from those produced by a 100‐Hz Gaussian masker, but differed significantly from those produced by 100‐Hz‐wide multiplication noise. This result indicates that differences in masking between Gaussian and multiplication noise are not due to their different fine structure, but to their different envelope statistics.

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The role of envelope fluctuations in spectral masking

Two experiments were conducted to investigate the perception of structural boundaries in six popular music songs. In the segmentation experiment, participants were asked to indicate perceiv...

AG Armin Kohlrausch

Papers

Noise disturbance in open-plan study environments: a field study on noise sources, student tasks and room acoustic parameters.

Perceptual evaluation of music similarity.

Auditory-visual interaction : From fundamental research in cognitive psychology to (possible) applications

The role of envelope fluctuations in spectral masking

The perception of structural boundaries in melody lines of Western popular music