bluuebunny/crossref_metadata_2025 huggingface dataset:
A multibeam subbottom profiler
Authors: Caruthers Jerald W.
Published: October 2013

A multibeam subbottom profiling system (MSBPS) is being built with funding from the Defense University Research Instrumentation Program (DURIP) in coordination with the Office of Naval Research. The MSBPS is being constructed from three T70 Neptune Sonar transducer modules in a line. Each T70 has five 11.5-kHz elements in each of two parallel lines. The resulting system is composed of 15 elements in each line with a total length of 1.3 m separated by about 8.5 cm. Each line has full beamwidths to the 3-dB points of about 5×70 deg. The system will be used in an interferometric mode between the two lines. [This work is supported by ONR 321OA.]
Using ambient noise and vector sensor arrays to form a subbottom profiler
Authors: Hursky Paul , Siderius Martin
Published: October 2013

Surface-generated ambient noise is distributed in time, but its correlation produces a strong impulse that is excellent for imaging the ocean floor. This technique has been experimentally demonstrated using vertical line arrays of pressure phones. The up-looking endfire beam (for ambient noise traveling down) is cross-correlated with the down-looking endfire beam (for the ambient noise reflected from the bottom, traveling up). Each layer in the bottom produces a distinct reflection. Previous work has required somewhat large vertical arrays. A towed horizontal array would be much better and allow us to make measurements with a mobile platform. The problem is that a horizontal line array cannot distinguish up from down—a broadside beam is symmetric with respect to the axis of the array. Vector sensors, sensing both pressure and particle velocity, have additional degrees of freedom for overcoming such ambiguities. We will show how vector sensors make it possible to implement such an ambient noise subbottom profiler, either in a greatly reduced vertical array or in a horizontal (towed) array configuration. We will also show results of processing data collected on a four-element vector sensor array and a much larger pressures-only array during the Makai experiment.
Development of practical broadband magnetohydrodynamic transducers for undersea digital communication
Authors: Berkenpas Eric , Jaskolski Corey
Published: October 2013

Demand for broadband underwater digital communication is being driven by development of tetherless autonomous underwater vehicles (AUVs). Current communications methods employ typically piezoelectric transducers. While efficient, and broadband as receivers, these transducers exhibit significant frequency dependence when transmitting, thus limiting their utility in digital communications. Magnetohydrodynamic (MHD) transducers generate acoustic waves in seawater by applying time-varying Lorentz force to moving ionic charges in the presence of a magnetic field. MHD transducers are ultracompliant, exhibit wide-frequency bandwidth, and are therefore attractive for high-speed undersea digital communications. This paper reports on exploratory development MHD transducers with the goal of improved transduction efficiency and bandwidth. Novel MHD transducer structures were fabricated with permanent magnet, parallel electrode structures, and planar interdigitated electrode structures. To evaluate transducer performance, an automated transducer test setup was assembled incorporating a 7500-L saltwater test environment, a time-gated high-current signal source, and a wideband hydrophone. Use of acoustic baffles and waveguides was also investigated. A theoretical discussion is also included. This work represents the practical employment of MHD transducers to undersea digital communication. [Work supported by General Atomics.]
Spectro-temporal analysis of Palauan chants
Authors: Abels Birgit , Braasch Jonas
Published: October 2013

A field study was carried out to determine how songs from the repertory of chants in Palau have changed over the last century. To this end, several chanters were recorded during recent fieldwork; these sound documents were then compared to items from several historic collections of sound recordings from the Phonogram Archives Berlin, Germany, and the Pacific Collection, Library of the University of Hawai’i at Manoa. The available recordings cover the time span from 1909–2006. Analytical results were derived in the form of spectrograms both for recent recordings from the years 2005/2006 and historic ones from 1963. They confirmed the auditory impression that chanting in Palau today has moved away from a recitative style, relying predominantly on the speaking voice, towards a performance practice the sound ideal of which is the singing voice. Also, the range of pitch employed in these chants has expanded. Spectral analysis also revealed how, in particular genres, the musical form of group chants is structured by the changing contours of a frequency band that is resolved at phrasal ends, when the singers narrow the range of this tonal cluster. This unique technique is one of the core musical elements of the Palauan singing tradition.
Spectral modification technique in conversion of musical notes or tempos for singing voice synthesis system
Authors: Banno Hideki , Ohta Kumi , Kawazoe Masato , Itakura Fumitada
Published: October 2013

The STRAIGHT time-frequency representations (spectrograms) of singing voice signals in various musical notes and various tempos are observed to develop a high-quality synthesis system of singing voice. The spectrogram of STRAIGHT, which is a very high-quality analysis-synthesis system, can represent the vocal tract information accurately. A conversion system of a musical note or a tempo of an input singing voice signal has been implemented based on the observation. As a result of the observation, the frequency warping of the STRAIGHT spectrogram based on a DP matching algorithm has been introduced into the system. It was found that the method using a differential of a smoothed spectrum as a spectral distance measure in the frequency warping produces subjectively better quality than that using a smoothed spectrum directly. It was also found that the method without spectral modification, i.e., only with pitch/tempo modification in the conversion, produces better quality than that using a differential of a smoothed spectrum. This can be caused by the destruction of naturalness in the method using a differential of a smoothed spectrum.
Automatic detection of head voice in sung musical signals via machine learning classification of time-varying partial intensities
Authors: Cassidy Ryan J. , Mysore Gautham J.
Published: October 2013

The automatic detection of portions of a musical signal produced according to time-varying performance parameters is an important problem in musical signal processing. The present work attempts such a task: the algorithms presented seek to determine from a sung input signal which portions of the signal are sung using the head voice, also known as falsetto in the case of a male singer. In the authors’ prior work [Mysore et al., Asilomar Conf. Signal. Sys. Comp. (2006) (submitted)], a machine learning technique known as a support vector classifier [Boyd and Vandenberghe, 2004] was used to identify falsetto portions of a sung signal using the mel-frequency cepstral coefficients (MFCCs) of that signal (computed at a frame rate of 50 Hz). In the present work, the time-varying amplitudes of the first four harmonics, relative to the intensity of the fundamental, and as estimated by the quadratically interpolated fast Fourier transform (QIFFT) [Abe and Smith, ICASSP 2005], are used as a basis for classification. Preliminary experiments show a successful classification rate of over 95% for the QIFFT-based technique, compared to approximately 90% success with the prior MFCC-based approach. [Ryan J. Cassidy supported by the Natural Sciences and Engineering Research Council of Canada.]
A proposal of discrimination method between voice and music using Gaussian mixture models and similarity in a music selection
Authors: Yoshida Takuma , Ishigame Masaaki , Ito Yoshiaki , Kojima Kazunori
Published: October 2013

We have proposed a method for automatic music boundary detection using similarity in a music selection. The method is able to capture a whole position of a consecutive music selection, although the boundary position of a music selection is likely to be roughly estimated. In this paper, we propose a new method that combines a GMM (Gaussian mixture model) discrimination method between music and voice with the previously proposed method. The GMM enables us to determine strict boundary positions. On the other hand, the GMM often misdetects boundaries that are not actual boundaries, such as changing points of music instruments, the point of modulation in a music selection, and so on. We, therefore, exclude the GMM misdiscrimination in a music selection by the previously proposed method, and also realize the precise detection of music boundaries by the GMM. We conducted various experiments using open music selections that are provided by RWC, and the results showed the proposed method could improve the performance of music boundary detection, compared with the previous method and the method using only the GMM.
The effect of seating arrangement on choral sound in a nonselected mixed collegiate choral ensemble
Authors: Wang Wei-Chun
Published: October 2013

With both macroarrangement concerns and microarrangement concerns, choral directors use singer’s placement as an essential technique to find compatible voices by listening to individual voices in various combinations. This study investigated the effect of seating arrangements, musical textures, and language familiarity on the choral balance and choral blend in an inexperienced collegiate choral ensemble. After ten rehearsals directed by the investigator, 48 nonselected choristers of a curricular SATB choral ensemble sang four musical excerpts, with the combination of two musical textures (homophonic and polyphonic compositions) and two types of languages (native and foreign language), a cappella in three formations (a sectional block, a mixed quartet, and a hybrid formation) in a chapel. Five experienced judges evaluated the screened live performance by rating the choral balance and choral blend on seven-point scales. The process was repeated. For blend only, sectional and hybrid formations were favored for polyphonic excerpts. The excerpts sung in native language were rated higher than the foreign excerpts, in particular for blend.
Infrasound associated with stratospheric ash injection, window-shattering explosions, and incandescent avalanches at Tungurahua Volcano, Ecuador
Authors: Garces Milton , Fee David , McNamara Sara , McCormack David , Bass Henry E.
Published: October 2013

On July 14, 2006, Tungurahua volcano in Ecuador initiated a dramatic eruptive sequence that caused the evacuation of villagers, the destruction of crops, and the reports of ash clouds above 15 km. Acoustic signals have been recorded by the prototype infrasound acoustic-surveillance system (ASHE) currently operating in Ecuador. The infrasonic signals recorded by the ASHE included explosions, pyroclastic flows, and a sustained low frequency vibration of the ground. We present the features of the different types of eruption signals, and discuss the physics of eruptive processes and volcanic ash injection into the atmosphere. We also compare the July 2006 ash-rich eruption sequence with the May 2006 eruptive episode, which injected very little ash into the atmosphere. Results are of significance for the future operational use of acoustic monitoring of volcanic activity for aviation safety.
The deep sound of one wave plunging
Authors: Garces Milton , Fee David , McNamara Sara , Aucan Jerome , Merrifield Mark
Published: October 2013

The ability to provide infrasound estimates of breaking ocean wave height and period in shallow reefs, steep rocky coastlines, and sand beaches has been demonstrated in previous work. Yet defining the source process and isolating the source pressure function remained elusive because of ambiguity introduced by complex coastlines and multiple breaker zones. Due to the steep bathymetry and the its proximity to land, the Temae reef in the northeast coast of Moorea island, French Polynesia, provided a well constrained experimental environment where individual breaking waves could be identified and recorded. Synchronous wave height, infrasonic, seismic, and visual recordings of individual waves breaking against the shallow reef ledge were made and correlated. We characterize a possible source mechanism for surf infrasound and demonstrate the capability to acoustically track alongshore traveling (peeling) plunging waves. We also introduce preliminary results on remote infrasonic monitoring of the surf zone in the North Shore of Hawaii during the 2006-07 Winter high surf season.
Low-frequency acoustic propagation in a shallow water internal wave field
Authors: Edelmann Geoffrey F. , Lingevitch Joseph F. , Calvo David C.
Published: October 2013

A fully 3-D parabolic equation is used to simulate low-frequency acoustic propagation through a nonlinear internal wave field. Previous simulations have shown that acoustic propagation is dependent on the relative orientation between the direction of the internal wave train and the acoustic signal. When the acoustic and internal waves are parallel, a simple 2-D vertical refraction is the dominant interaction. As the two waves become perpendicular, horizontal refraction of the acoustic signal due to azimuthal coupling has been suggested [Frank et al., J. Acoust. Soc. Am. 118, 723–734 (2005)]. Comparisons of 3-D acoustic propagation through an internal wave field with and without azimuthal coupling will be made. The parabolic equation used makes a narrow angle operator approximation in azimuth and a wide angle approximation in depth. We will extend the previous work such that coupling in both the horizontal and vertical direction will be calculated simultaneously. [This work is supported by the Office of Naval Research.]
Infrasonic wave observations at Fairbanks, AK, of Augustine volcano eruptions during January 2006
Authors: Wilson Charles , McNutt Steve , Olson John , Tytgat Guy
Published: October 2013

The recent Augustine eruptions, from the 11th to the 28th of January 2006, have produced a series of ten infrasonic signals observed at the I53US array. The eruption times for the signals were provided by the Alaska Volcanic Observatory at UAF using a Chaparral microphone present on Augustine Island a few kilometers from the crater. The bearing and distance of Augustine from I53US are respectively 207.8 deg and 675 km. The analysis of the signals is done with a least-squares detector/estimator that calculates, among other things, the horizontal trace-velocity and the azimuth of arrival of the signal. The average values of the trace-velocity and azimuth for all ten Augustine signals are 0.336±0.0136 km/s and 208.7±1.5 deg. respectively. The celerity for each signal was calculated using the range 675 km and the individual travel times to I53US. The average celerity for all ten eruption signals was 0.287±0.018 km/s. Ray tracing studies, using wind speed and temperature profiles supplied by Dr. Doug Drob at NRL, have shown that both stratospheric and thermospheric ray paths are present in the data set.
Osmium’s full elastic tensor between 5 K and 300 K
Authors: Pantea Cristian
Published: October 2013

Reported values of the zero-pressure bulk modulus of Os are both above and below that of diamond, creating a controversy as to which is the least compressible material. This work is another such study, but using two measurement techniques on two types of Os specimens. The full elastic tensor for osmium was measured using resonant ultrasound spectroscopy between 5 K and 300 K on polycrystalline and monocrystalline specimens and confirmed at ambient temperature using a pulse-echo-overlap measurement. It was found that osmium is more compressible than diamond (bulk modulus: 405 GPa for Os, versus 442 GPa for diamond). The independent elastic moduli of osmium are in relatively good agreement with the theory of Fast [Phys. Rev. B 51, 17431 (1995)]. However, the Debye temperature determined from low-temperature monocrystal elastic-moduli measurements extrapolated to 0 K disagrees with most previous reports and is in good agreement with one specific-heat measurement.
Excitation of elastic and capillary waves by electric field tweezers and its application to material characterization
Authors: Hosoda Maiko , Ogawa Hideo , Nomura Hiroyasu
Published: October 2013

We recently developed the electric tweezers system to excite the surface vibration for the measurement of local mechanical properties of soft condensed materials. A periodical electric field applied onto the material surface by a conductive thin needle induces the Maxwell stress and picks up the sample surface. We can determine the shear elasticity of the sample from the absolute displacement of the deformation, and the viscosity from its dynamic response, respectively. The numerical simulation predicts that the electric voltage of 100 V applied to the gap of 100 Em between the needle edge and surface induces the deformation of several nm, which was experimentally confirmed by the optical lever technique. The remarkable feature of the system is that the characteristic scale of the surface deformation, such as the depth and width of the medium motion, is dominated by the gap and, therefore, we can uniquely determine the complex mechanical impedance and the surface energy by observing the dynamic surface response in a wide range of the gap and oscillation frequency. The system was applied to the gelatin gel at various concentrations and we found the results obtained are well explained by the previously known complex elasticity of the material.
Hypersonic phononic crystals
Authors: Gorishnyy Taras , Ullal Chaitanya K. , Maldovan Martin , Thomas Edwin L. , Jang Ji-Hyun
Published: October 2013

Phononic crystals are structures with spatially periodic variations in density and sound velocities. The most fascinating feature of phononic crystals is the existence of stop bands or band gaps in their dispersion relation, where no phonons are allowed to propagate. As a result, phononic crystals have great promise for achieving precise control over propagation of sound and other mechanical waves. In this talk our recent investigation of 2-D and 3-D hypersonic phononic crystals with band gaps in GHz frequency range will be presented and their potential applications as acoustic mirrors, lenses, waveguides, etc. will be discussed. High-quality single-crystalline structures were fabricated using interference lithography. Their phonon dispersion relation was directly measured with Brillouin light scattering. Finite-element analysis was employed to compute theoretical dispersion relation and provide interpretation for the experimentally observed propagation modes [T. Gorishnyy et al., Phys. Rev. Let. 94, 115501 (2005); T. Gorishnyy et al., Physics World 18 (12), 24–29 (2005)]. [Work supported by NSF Grants DMR-0308133 and DMR-0414974.]
Improving quality of small body transmitted ordinary speech with statistical voice conversion
Authors: Sekimoto Hidehiko , Toda Tomoki , Saruwatari Hiroshi , Shikano Kiyohiro
Published: October 2013

The explosive spread of cellular phones enables us to communicate with each other at any time or place. Although cellular phones are convenient, there are still some problems. For example, it is difficult to send intelligible speech under noisy conditions, which is a fatal problem especially when talking privately using small speech in crowds. To improve the quality of small speech under such situations, a new speech communication style is proposed using a nonaudible murmur (NAM) microphone [Nakajima et al., Eurospeech (2003), pp. IV-2601–2604]. The NAM microphone is robust to eternal noise, although body transmission causes quality degradation. In this paper, to improve the sound quality of small body transmitted ordinary speech (SBTOS), which is small speech recorded with a NAM microphone, two conversion methods that reflect a statistical voice conversion method based on Gaussian mixture models (GMMs) [Toda et al. Interspeech (2005), pp. 1957–1960] are conducted. One conversion method is from SBTOS to ordinary speech (SBTPS-to-SP), and the other is from SBTOS to small speech (SBTOS-to-SSP). SBTOS-to-SSP has more consistent correspondence of voiced/unvoiced segments between input and output speech than SBTOS-to-SP. The results of objective and subjective evaluations show that SBTOS-to-SSP outperforms SBTOS-to-SP.
Evaluation of eigenvoice conversion based on Gaussian mixture model
Authors: Ohtani Yamato , Toda Tomoki , Saruwatari Hiroshi , Shikano Kiyohiro
Published: October 2013

Eigenvoice conversion (EVC) has been proposed as a new framework of voice conversion (VC) based on the Gaussian mixture model (GMM) [Toda et al., ‘‘Eigenvoice Conversion Based on Gaussian Mixture Model,’’ ICSLP, Pittsburgh, Sept. 2006]. This paper evaluates the performance of EVC in conversion from one source speaker’s voice to an arbitrary target speakers’ voices. This framework trains canonical GMM (EV-GMM) in advance using multiple parallel data sets consisting of utterance pairs of the source and many prestored target speakers. This model is adapted to a specific target speaker by estimating a small number of free parameters using a few utterances of the target speaker. This paper compares spectral distortion between converted and target voices in EVC with conventional VC based on GMM when varying the amount of training data and the number of mixtures. Results show EVC outperforms conventional VC when using small amounts of training data. EVC can effectively train a complex conversion model using the information of many prestored speakers. By contrast, conventional VC needs a large-sized parallel data set for training. It also shows the results of subjective evaluations of speech quality and conversion accuracy for speaker individuality.
Evaluating naturalness of speeches morphed by independently using the interpolation ratios of the time-frequency axes and amplitude
Authors: Takahashi Toru , Morise Masanori , Irino Toshio
Published: October 2013

In speech morphing procedure [Kawahara et al., Proc. IEEE-ICASSP 2003, Vol. I, pp. 256–259], two parameters exist for controlling the degree of morphing between the source and target: the interpolation ratios of the time-frequency axes and amplitude. Conventional morphing methods use only a single path in which both ratios are identical. It has, however, been reported that perception of naturalness degrades around a morphing ratio of 0.5. It was assumed that there would be better combination of the ratios with maintaining the quality. It was surveyed that the naturalness contour is within a two-dimensional morphing space. The morphed speech sounds are synthesized in combinations of 11 axis ratios (between 0 and 1 by 0.1 step) and 11 amplitude ratios. Synthetic sounds (121 in all) were presented to subjects to judge the naturalness rate. The optimum path will be described at a presentation to be given at this conference. [This research was partly supported by the ‘‘e-Society Leading Project’’ of the Ministry Education, Culture, Sports, Science, and Technology.]
Vector-based language generation for associatively evoking environmental images
Authors: Aikawa Kiyoaki , Iida Akemi
Published: October 2013

A novel language generation method was proposed for spoken dialogue systems. The method selected verbal expressions for sensory inputs using a vector-based method. A weather-reporter system was implemented with seven input categories of weather parameters including temperature, humidity, wind velocity, and cloud cover. The system selected the most appropriate short phrase for representing the measured weather parameters to let the listener associatively imagine the reporter’s weather condition descriptions. The system included 149 short phrases for weather expressions, each represented by a 62-element vector called the template vector. Given the 62-element input vector for a set of weather parameters, one or two phrases were selected based on the similarity measured between the input and template vectors. The system was able to produce an expression by combining a couple of phrases. A dissimilarity measuring algorithm was proposed to assign the conjunction ‘‘and’’ or adversative ‘‘but’’ automatically to conjoin two phrases. A bilingual capability was also added for enabling the system to output English and Japanese phrases. For English outputs, sentence-initial phrases were added to the selected phrases depending on the similarity value, while sentence-finals were added for Japanese outputs. Evaluation experiments showed that automatic conjunction assignment can function with high reliability.
Enhancement of electrolaryngeal speech by spectral subtraction with minimum statistics-based noise estimation
Authors: Mitra Priyanko , Pandey Prem C.
Published: October 2013

Transcervical electrolarynx is a vibrator held against the neck tissue by a laryngectomy patient to provide excitation to the vocal tract, as a substitute to that provided by glottal vibrations. The electrolaryngeal speech suffers from lack of voicing and pitch control, low-frequency deficiency, and presence of background noise, caused by leakage of acoustic energy from the vibrator and vibrator-tissue interface. Pitch-synchronous application of spectral subtraction has been used for reducing the self-leakage noise, with averaging-based noise estimation on an initial segment with closed lips. But, the leakage noise spectrum varies with speech production and vibrator orientation and pressure. A dynamic estimation of noise is carried out by using minimum statistics, with two-pitch period analysis frames and one period overlap. Minimum value of each spectral sample in a set of past frames is used for dynamically estimating the magnitude spectrum of noise. This is subtracted from the magnitude spectrum of noisy speech and the signal is reconstructed using the original phase spectrum. Smoothing of the estimated noise spectrum resulted in better noise cancellation. Quality of electrolaryngeal speech is further enhanced by spectral deficit compensation of the magnitude spectrum.
Speech detection using Real Adaboost in car environments
Authors: Takiguchi Tetsuya , Matsuda Hiroyoshi , Ariki Yasuo
Published: October 2013

In real noisy environments, a speech detection algorithm plays an especially important role for noise reduction, speech recognition, and so on. In this paper, a speech/nonspeech detection algorithm using Real Adaboost is described, which can achieve extremely high detection rates. Boosting is a technique of combining a set weak classifiers to form one high-performance prediction rule, and Real Adaboost [R. E. Schapire and Y. Singer, Mach Learn. 37, 3, 297–336, (1999)] is an adaptive boosting algorithm in which the rule for combining the weak classifiers adapts to the problem and is able to yield extremely efficient classifiers. The Real Adaboost algorithm is investigated for speech/nonspeech detection problem. The proposed method shows an increasing speech detection rate in car environments, comparable with that of the detector based on GMM (Gaussian mixture model), where the detection accuracy rate was 98% for the proposed method and 92% for GMM in a car at highway speed. The results of the experiments clarified the effectiveness of the proposed method.
Nonrestrictive and long-term monitoring system of utterance and a laughing voice: Laughometer
Authors: Matsumura Masafumi , Kawabata Yutaka , Suzuki Ryoji , Yoshida Masaki
Published: October 2013

It is said that laughter is the best medicine. Laughter is known to be effective for relieving stress and promoting health. Therefore, this study is intended to clarify the relationship between laughter and physiological factors related to health promotion. We developed a hands-free wireless system (Laughometer) that monitors laughter (a laughing voice) in everyday conversations. This Laughometer detects vocal cord vibrations using a bone-conductive microphone attached to the skin on the neck. Based on data from repeated vocalizations of laughter, this apparatus can distinguish features of laughter in everyday conversations. Based on the mean fluctuation (standard deviation) in syllable intervals, 90% of laughs are differentiable from normal conversation. While attending a live rakugo comedy show, the number and duration of laughs were monitored by analyzing laryngeal voice (approximately 1-h duration). The mean differentiation rate for laughing voice was 94%, thereby confirming the efficacy of laughter recognition based on fluctuation in syllable intervals.
Development of nonvoice dialogue interface for robot systems
Authors: Nisimura Ryuichi , Hashizume Aki
Published: October 2013

In this presentation, a nonvoice dialogue interface scheme for robot systems to improve the flexibility of human-robot interaction is proposed. A prototype system with a microphone in a plastic doll has been developed to examine its potential for distinguishing interaction noises and human utterances. It realizes a simple, one-input one-response interaction with perception of a user’s action. For example, the system can reply ‘‘Ouch!’’ when its body or head is beaten by a user. It is also able to make a response to a calling by the voice. This scheme would provide a new interaction style, unlike conventional spoken dialogue systems in which a user’s rough actions were treated as meaningless obstacles. It identifies the source of noises based on GMM (Gaussian mixture model) noise recognition [A. Lee et al., Proc. INTERSPEECH, 1, 173–176 (2004)]. Thirteen-class GMMs were constructed from voices and noises like slapping or stroking the head, and knocking the body, which were recorded via trial testing the prototype system. It is possible to discriminate noises and utterances by comparing acoustic likelihoods from GMMs. The experiment investigates performances of acoustic feature vectors consisting of MFCC (mel frequency cepstral coefficients) to identify interaction noises.
Application of harmonic plus noise model for enhancing speaker recognition
Authors: Gangula Gidda Reddy , Pandey Prem C. , Lehana Parveen K.
Published: October 2013

Speaker recognition systems mostly employ mel frequency cepstral coefficients (MFCC). Performance of these systems is generally affected by background noise, transmission medium, etc. Further, they do not perform well in text-independent environment with limited training data. For enhanced performance, the set of parameters used should separate the speaker-dependent information from the linguistic information. Towards this end, application of parameters of the harmonic plus noise model (HNM)-based analysis is investigated. HNM divides the speech spectrum into harmonic and noise bands separated by a dynamically varying maximum voiced frequency. This frequency is a speaker-dependent parameter and its estimation is not affected by moderate SNR degradation. A speaker recognition system was devised using three HNM parameters, namely, maximum voiced frequency, relative noise band energy, and pitch. It gave-performed comparably to that of MFCC-based recognition, for a group of ten speakers. An enhanced performance was observed by using MFCC and the three HNM parameters together, indicating the suitability of HNM for speaker recognition.
Noisy speech recognition based on codebook normalization of discrete-mixture hidden Markov models
Authors: Kosaka Tetsuo , Models hidden Markov , Katoh Masaharu , Kohda Masaki
Published: October 2013

This paper presents a new method of robust speech recognition under noisy conditions based on discrete-mixture HMMs (DMHMMs). The DMHMMs were proposed originally to reduce calculation costs. Recently, we applied DMHMMs to noisy speech recognition and found that they were effective for modeling noisy speech [Kosaka et al., Proc. of ICA04 (2004), Vol. II, pp. 1691–1694]. For further improvement of noisy speech recognition, we propose a novel normalization method for DMHMM codebooks. The codebook normalization method is based on histogram equalization (HEQ). The HEQ is commonly applied for feature space normalization. The DMHMM codebooks were normalized in this study. Therefore, this method is considered as normalization not in feature space, but in model space. Some merits are inherent in choosing model space normalization. In model space normalization, a transformation function can be prepared for each acoustic model. In addition, it is not necessary to normalize input parameters frame-by-frame. The proposed method was compared with both conventional continuous-mixture HMMs (CHMMs) and DMH-MMs. That comparison showed that the proposed method obtained the best performance: an average relative improvement of 29.2% over the CHMM baseline.
Robust speech recognition for home environments using factorial hidden Markov models
Authors: Betkowska Agnieszka , Shinoda Koichi , Furui Sadaoki
Published: October 2013

In this paper we present a speech recognition system for the home environment that is robust to nonstationary sudden noise such as doors slamming, knocking, and falling objects. This noise appears rapidly and lasts for a short period of time. Additionally the SNR is difficult to estimate. As a compensation model for this task, we investigated the use of the factorial hidden Markov model (FHMM) architecture proposed by Deoras (2004). In our method, a hidden Markov Model (HMM) for each word in a dictionary and an HMM for sudden noise are employed to build a factorial HMM to recognize noisy speech. Since the factorial HMM defined by Deoras applies only to static features of the observation vector during the recognition process, we extended it to work with dynamic features. The proposed method was evaluated with a database recorded by a personal robot, PaPeRo, in the houses of 12 Japanese families. The experiments were conducted for both synthesized speech (at different SNRs) and real noisy speech, which was recorded by the robot. In both cases, our method showed significant improvement over HMMs trained with clean speech data.
A phoneme duration model considering speaking-rate and linguistic features for speech recognition
Authors: Ohkawa Yuichi , Ito Akinori , Suzuki Motoyuki , Makino Shozo
Published: October 2013

In this paper, we proposed a method of phoneme duration modeling for speech recognition. A phoneme with extremely short or long duration often causes a decline of performance of speech recognition. In order to improve performance of recognition, an estimation of phoneme duration determined by various parameters is required. However, there was no usual method of duration modeling for speech recognition considering the influence of both speaking-rate and linguistic feature (phoneme location in sentence, part-of-speech, et al.), which influence phoneme duration strongly. Therefore, we modeled influence of speaking-rate by two-dimensional normal distribution of phoneme duration and local average of vowel duration. Each normal distribution is determined by tree-based clustering with various questions, which include linguistic feature. With an experiment of estimation of phoneme duration by this model, we acquired 20.8% reduction of standard deviation of estimation error. We also used the proposed duration model for rescoring of N-best hypothesis of speech recognition. With an experiment of rescoring of recognition results for spontaneous speech, we acquired significant reduction of 4.7% in phoneme error rate.
Investigation of model-based error rate estimation techniques for speaker-independent large-vocabulary recognition tasks
Authors: Kai Atsuhiko , Nakamori Shoji
Published: October 2013

This paper proposes model-based error rate estimation techniques for HMM-based speech recognition systems and shows their effectiveness in several speaker-independent task conditions. The proposed techniques are based on an HMM-based error rate estimation method [C.-S. Huang et al., IEEE Trans. SAP, 11, No. 6, 581–589 (2003)], which only depends on subword-based pronunciation lexicon knowledge. This study assumes the need of the dynamic change of open vocabulary. The vocabulary size is varied between 5000 and 25000 words. Two types of formalizations are investigated. They utilize the Bhattacharyya distance as a local distance measure between two competing word classes which are modeled by syllable-unit HMMs. A misclassification measure, which is similar to the one used by minimum classification error (MCE) training methods, is used for estimating error rate. The correlation between the error rates for testing utterances by 20 speakers and the estimated error rates for varied vocabulary sizes are evaluated. Except for one speaker, the correlation coefficient above 0.8 was obtained for both proposed formulations. Moreover, when the uttered words are clustered to five coarse classes of different estimated error rates, the correct rate of relative consistency between those adjacent classes was above 90% on average.
An investigation of early reflection signal based on impulse response on automatic speech recognition
Authors: Hirano Yoshiki , Denda Yuki , Nakayama Masato , Nishiura Takanobu
Published: October 2013

Early reflection signals (especially, within 50 ms from direct sound arrival) are useful to speech listening for human being. On the other hand, the higher the reflection energy becomes, the more present automatic speech recognition performance decreases, subject to using clean acoustic phoneme model. However, it was not clear that early reflections are useful or useless to recognize the speech on distant-talking speech recognition, because reverberation time was employed as reverberation criterion. It is a unique time and does not depend on source position in a room. In addition, it can only express the time in which sound attenuation becomes −60 dB and cannot express the early reflection that strongly influences speech recognition performance. Therefore, it should be nonsuitable reverberation criterion for distant-talking speech recognition. To overcome this problem, we investigate the relation between early reflections and distant-talking speech recognition performance based on impulse response between talker and microphone towards newly suitable reverberation criterion on distant-talking speech recognition. As a result of evaluation experiments in real acoustic environments, we could confirm the relation between speech recognition performance and early reflection signals. In future work, we will try to propose the newly suitable reverberation criterion. [Work supported by MEXT of Japan.]
Towards an efficient archive of spontaneous speech: Design of computer-assisted speech transcription system
Authors: Nanjo Hiroaki , Kawahara Tatsuya
Published: October 2013

Computer-assisted speech transcription (CAST) system for making archives such as meeting minutes and lecture notes is addressed. For such a system, automatic speech recognition (ASR) of spontaneous speech is promising, but ASR results of spontaneous speech contain a lot of errors. Moreover, the ASR errors are essentially inevitable. Therefore, it is significant to design a good interface with which users can correct errors easily in order to take advantages of ASR for making speech archives. It is From these points of view that our CAST system is designed. Specifically, the system has three correction interfaces: (1) pointing device for selection from competitive candidates, (2) microphone for respeaking, and (3) keyboard. One of the most significant correction methods is selection from competitive candidates, thus more accurate competitive candidates are required. Therefore, generation methods of competitive candidates are discussed. Then, a speech recognition strategy (decoding method) based on the minimum Bayes-risk (MBR) framework is discussed. Since MBR decoding can distinguish and deal with content words and functional words, which are conventionally treated in a same manner, the approach is expected to generate more content words in competitive candidates.
Acoustic modeling of spontaneous speech of Japanese preschool children
Authors: Shindo Izumi , Cincarek Tobias , Toda Tomoki , Saruwatari Hiroshi , Shikano Kiyohiro
Published: October 2013

In recent years, there is an increasing demand for speech recognition of children. However, the recognition of children’s speech, especially preschool children (2 to 5 years of age), is very difficult. For example, recognition accuracy using a children’s acoustic model provided by the Japanese Dictation Toolkit is only 21.4%. Many different variations of child speech with palatal sounds and pronunciation error decrease recognition performance. This paper proposes a recognition method that investigates the characteristics of preschool children’s speech using experimental data and considers phonetic changes. Mapping between standard and altered pronunciations of words is determined. In experiments, a large amount of spontaneous child speech (2 to 15 years of age) was collected with the speech-oriented public guidance system, ‘‘Takemaru-kun,’’ which is currently available. Recognition performance increases to 49.2% by acoustic model adaptation of preschool children’s speech. When allowing multiple pronunciation variations per word during recognition, further improvement to 52.0% is achieved.
Collection of multimodal data in real-world driving
Authors: Kusakawa Takashi , Miyajima Chiyomi , Nishino Takanori , Itou Katsunobu , Takeda Kazuya
Published: October 2013

Our research group has recently developed a new data collection vehicle equipped with various sensors for the synchronous recording of multimodal data including speech, video, driving behavior, and physiological signals. Driver speech is recorded with 12 microphones distributed throughout the vehicle. Face images and a view of the road ahead are captured with three CCD cameras. Driving behavior signals including gas and brake pedal pressures, steering angles, vehicle velocities, and following distances are recorded. Physiological sensors are mounted to measure the drivers’ heart rate, skin conductance, and emotion-based sweating on the palm of the hand and sole of the foot. The multimodal data are collected while driving on city roads and expressways during four different tasks: reading random four-character alphanumeric strings, reading words on billboards and signs seen while driving, interacting with a spoken dialogue system to retrieve and play music, and talking on a cell phone with a human navigator using a hands-free device. Data collection is currently underway. The multimodal database will be published in the future for various research purposes such as noise-robust speech recognition in car environments, detection of driver stress while driving, and the prediction of driving behaviors for improving intelligent transportation systems.
Marking up Japanese Map Task Dialogue Corpus
Authors: Ohsuga Tomoko , Itahashi Shuichi , Tutiya Syun
Published: October 2013

This presentation reports an outline of marking up the Japanese Map Task Dialogue Corpus. The project was conducted by an independent group of researchers from the faculties of Chiba University and other institutions. This corpus contains 128 dialogues by 64 Japanese native speakers. The basic design of the dialogues and recordings conform to the original HCRC Map Task Corpus of the University of Edinburgh. Two speakers participated in the map task dialogues; an instruction giver who has a map with a route and an instruction follower who has a map without a route. The giver verbally instructs the follower to draw the route on his/her map. The corpus is marked up according to XML-based TEI (Text Encoding Initiative) P5 format, which is developed in an effort to provide interchangeable and shareable text data. The transcriptions of TEI format are viewed as ‘‘tags‘‘ that describe the start and end times of utterances, the duration of pauses, nonverbal events, and synchronization of overlapping utterances. This corpus will be available through NII-SRC (Speech Resources Consortium).
How blind are we in blind signal processing?
Authors: Kellermann Walter
Published: October 2013

Blind signal processing algorithms aim at blindly solving classical signal processing problems such as system identification, signal separation, or source localization. Here it is investigated to which extent some of the more popular blind signal processing concepts are really blind when they are used for signal acquisition in the acoustic domain. Blindness regarding the source configuration and the source signal properties, blindness with respect to channel properties, and, finally, blindness regarding the microphone configuration are investigated. It turns out that many algorithms are explicitly nonblind with respect to important properties of the source configuration, such as the number of sources and their pointlike nature. The source signals typically have to fulfill certain statistical properties or have to meet sparseness constraints. Some algorithms rely on a dominant direct acoustic path between sources and sensors, and linearity of the transmission channel model is implied with all convolutive mixture models. Finally, some popular algorithms are actually aiming at direction of arrival estimation, which always requires knowledge on the microphone array geometry. In essence, blind algorithms are wellinformed in many respects and are blind only with regard to a few, although decisive, properties.
Blind deconvolution for noisy dynamic channels
Authors: Roan Michael J.
Published: October 2013

It is common in acoustics to measure a signal that has been degraded by propagation through an unknown, noisy channel prior to measurement. While only the degraded measured signal is available, the data of interest are the original signal and the channel parameters. Often, it is desirable to reverse the filtering process by application of an inverse filter to recover the original signal. When neither the input signal properties nor the channel properties are known, this process is known as blind deconvolution (BDC). Typically, BDC algorithms assume noiseless, stationary propagation channels and input sources. These assumptions are usually violated in practical applications (e.g., noisy multipath propagation environments with moving source and receiver). To model these effects, predictive techniques are applied to incorporate a priori information about the system into the existing blind processing framework. The original contributions of this work follow. First, a novel formulation of the extended Kalman filter (EKF) is proposed. This allows incorporation of a priori information into gradient-based blind processing algorithms. This formulation is then applied to the natural gradient (NG) BDC algorithm. Finally, results are presented that suggest significant improvement in signal recovery performance over the NG BDC algorithm for dynamic noisy channels.