Showing papers on "Noise published in 2006"

Effects of Bilingualism, Noise, and Reverberation on Speech Perception by Listeners with Normal Hearing

Abstract: This study compared monosyllabic word recognition in quiet, noise, and noise with reverberation for 15 monolingual American English speakers and 12 Spanish–English bilinguals who had learned English prior to 6 years of age and spoke English without a noticeable foreign accent. Significantly poorer word recognition scores were obtained for the bilingual listeners than for the monolingual listeners under conditions of noise and noise with reverberation, but not in quiet. Although bilinguals with little or no foreign accent in their second language are often assumed by their peers, or their clinicians in the case of hearing loss, to be identical in perceptual abilities to monolinguals, the present data suggest that they may have greater difficulty in recognizing words in noisy or reverberant listening environments.

A Swedish version of the Hearing In Noise Test (HINT) for measurement of speech recognition

Abstract: A Swedish Hearing In Noise Test (HINT), consisting of everyday sentences to be used in an adaptive procedure to estimate the speech recognition thresholds in noise and quiet, has been developed. The material consists of 250 sentences, with a length of five to nine syllables, normalized for naturalness, difficulty and reliability. The sentences were recorded with a female speaker. From the sentences, 25 phonemically balanced lists were created. All lists fluctuate less than 1 dB of the overall mean. The standard deviation of the test-retest difference is 0.94 dB when testing with one list, and decreases to 0.68 dB and 0.56 dB for two and three lists, respectively. The average speech recognition thresholds in noise for the Swedish sentences were -3.0 dB signal/noise ratio (SD=1.1 dB). The present study has resulted in a well-defined and internationally comparable set of sentences, which can be used in Swedish audiological rehabilitation and research to measure speech recognition in noise and quiet.

Synchronized and noise-robust audio recordings during realtime magnetic resonance imaging scans.

Abstract: This letter describes a data acquisition setup for recording, and processing, running speech from a person in a magnetic resonance imaging (MRI) scanner. The main focus is on ensuring synchronicity between image and audio acquisition, and in obtaining good signal to noise ratio to facilitate further speech analysis and modeling. A field-programmable gate array based hardware design for synchronizing the scanner image acquisition to other external data such as audio is described. The audio setup itself features two fiber optical microphones and a noise-canceling filter. Two noise cancellation methods are described including a novel approach using a pulse sequence specific model of the gradient noise of the MRI scanner. The setup is useful for scientific speech production studies. Sample results of speech and singing data acquired and processed using the proposed method are given.

Detection and suppression of wind noise in microphone signals

Abstract: To reliably and consistently detect desirable sounds, a system detects the presence of wind noise based on the power levels of audio signals. A first transducer detects sound originating from a first direction and a second transducer detects sound originating from a second direction. The power levels of the sound are compared. When the power level of the sound received from the second transducer is less than the power level of the sound received from the first transducer by a predetermined value, wind noise may be present. A signal processor may generate an output from one or a combination of the audio signals, based on a wind noise detection.

Responses to noise in urban parks and in rural quiet areas

Abstract: Nowadays the protection of quiet areas is an issue of increasing importance, as also recognized in the European Directive 2002/49/EC on the environmental noise [1]. Dealing with the demanded protection of quiet areas, it is important to characterize the soundscape of these environments properly, taking into account the multidimensionality of the individual perception which includes the effects of non-acoustic factors on subjective evaluation, such as visual impression and matching the personal expectation of the environment with the actual experience. This paper describes two experimental investigations carried out recently in Italy. The first deals with noise surveys and collection of subjective appraisals of three urban parks in Naples and the second consists of laboratory listening tests where sounds recorded binaurally in countryside parks have been mixed with sounds from some type of sources at different signal-to-noise ratios and played back by headphones to a group of subjects. The results obtained show that the subject's expectation to hear a sound in a specific environment, that is its congruence with the environment where it is heard, influences the corresponding annoyance. In particular, the more the sound is congruent with the expectation of the park, the less is the evoked annoyance and, conversely, the more is its acceptability. Furthermore, the acceptability of the sound increases with decreasing of its level and detectability of non natural sounds.

Content Fingerprinting Using Wavelets

Abstract: In this paper, we introduce Waveprint, a novel method for audio identification. Waveprint uses a combination of computer-vision techniques and large-scale-data-stream processing algorithms to create compact fingerprints of audio data that can be efficiently matched. The resulting system has excellent identification capabilities for small snippets of audio that have been degraded in a variety of manners, including competing noise, poor recording quality, and cell-phone playback. We explicitly measure the tradeoffs between performance, memory usage, and computation through extensive experimentation.

Road traffic noise in downtown area of tehran

Abstract: Noise pollution is a major problem for the quality of life in urban areas. The present study was conducted to determine the noise levels of road traffic at central area of Tehran. It focused on one of the busy and crowded square along with its 7 connecting streets, which had a heavy traffic and located in the downtown of the city. Total of 115 measuring points were selected along the roads, pavements and in the shopping areas to adequately represent the different acoustically commercial situations. The measuring points were divided in to 4 site-groups namely; Street, Pavement, Shop and Barrier each with 60, 40, 10, and 5 measuring points respectively. The measurements were carried out during a full week days started on Saturday morning and end on Friday evening. The A-weighted continuous equivalent sound level values, LAeq; LA max; LA min ; and the statistical levels: L1, L10, L50, L90 and L99 as well as the octave band center frequencies sound pressure levels were manually measured at each point separately. The mean values of LAeq for Street, Pavement, Shop and Barrier site groups were 78.5, 73.3, 68.7 and 70.8 dBA respectively and the overall mean of LAeq was 74.7 dBA. The statistical test (p<0.01) showed that the mean values for LAeq in all site groups as well as the overall mean value were higher than 65 dBA, which is the daytime governmentally prescribed noise limit for commercial areas. Comparing the individual measurements has also shown the 86.6% exceeded values from 65 dBA. The highest mean noise level in center frequencies upper than 1000 Hz was 71.5 dBA which was observed in the Street site group and the lowest one was 43.2 dBA in the Shop site group at 8000Hz center frequency. The corresponding values for the center frequencies lower than 1000 Hz were 78.2 and 66.1dBA at 63 and 500 Hz which were also observed in the Street and Shop site groups respectively. It can be concluded that the downtown of the city is environmentally noise polluted and the road traffic is the major source of it. Noting the noise emission standards, police control, and promoting the citizens awareness about the high level noise risk may help to relieve the noise problems in the city.

School Improvement: An Unofficial Approach

Abstract: Guide to acronyms Chapter 1 Introduction Chapter 2 Always winter and never Christmas Chapter 3 Just one piece of Turkish Delight? Chapter 4 Even the trees are on her side Chapter 5 Best keep down here Chapter 6 A strange sweet noise Recommended reading Notes References.

Frequency-Temporal Filtering for a Robust Audio Fingerprinting Scheme in Real-Noise Environments

Abstract: In a real environment, sound recordings are commonly distorted by channel and background noise, and the performance of audio identification is mainly degraded by them. Recently, Philips introduced a robust and efficient audio fingerprinting scheme applying a differential (high-pass filtering) to the frequency-time sequence of the perceptual filter-bank energies. In practice, however, the robustness of the audio fingerprinting scheme is still important in a real environment. In this letter, we introduce alternatives to the frequency-temporal filtering combination for an extension method of Philips' audio fingerprinting scheme to achieve robustness to channel and background noise under the conditions of a real situation. Our experimental results show that the proposed filtering combination improves noise robustness in audio identification. Keywords ⎯ Music information retrieval, audio fingerprint, frequency filtering, temporal filtering.

Method and apparatus for noise suppression

Abstract: In a noise suppression apparatus for suppressing noise contained in a speech signal, the speech signal is converted to a first vector of spectral speech components and a second vector of spectral speech components identical to the first vector. A vector of noise suppression coefficients is determined based on the first vector spectral speech components. A vector of estimated noise components is determined based on the first vector spectral speech components, and a speech section correction factor and a nonspeech section correction factor are calculated from the estimated noise components and the first-vector spectral speech components to produce a combined correction factor. The noise suppression coefficients are weighted by the combined correction factor to produce a vector of post-suppression coefficients. The second vector spectral speech components are weighted by the post-suppression coefficients to produce a vector of enhanced speech components.

Device and method for integrating sound effect processing and active noise control

Abstract: A device and a method for integrating 3D sound effect processing and active noise control are proposed. A digital signal processor incorporates an artificial reverberator and a 3D spatial audio processor into an audio module. The audio signal is presented via an earphone. Next, a microphone embedded in the vicinity of the loudspeaker inside the headset is used to sense an external noise while playing, and feed it back to an active noise controller, which generates an anti-noise to eliminate the external noise. Therefore, the signal to noise ratio can be increased and the 3D sound field effect can be significantly enhanced. In addition, a head-related transfer function is more efficiently implemented on the basis of an interaural transfer function in the spatial audio processing to reduce the filter order lower and hence the computation loading.

Removal of noise, corresponding to user input devices from an audio signal

Abstract: A noisy audio signal, with user input device noise, is received. Particular frames in the audio signal that are corrupted by user input device noise are identified and removed. The removed audio data is then reconstructed to obtain a clean audio signal.

A Perceptual Approach to Reduce Musical Noise Phenomenon with Wiener Denoising Technique

Abstract: Traditional denoising techniques, powerful in term of noise reduction, have the drawback of generating an annoying musical noise. This paper addresses the problem of enhancing speech in highly noisy environments using perceptual considerations. The post-processing technique we develop, considers the masking threshold of both noisy speech and the denoised one, to detect musical noise components. Next, to make them inaudible, detected musical noise candidates are set under the noise masking threshold and their closest neighbors are smoothed. Extensive subjective and objective tests have shown that, after enhancement, the musical noise is well reduced even at very low signal to noise ratios.

Audio input/output device and method for switching input/output functions

Abstract: Using a 4-pin audio jack, 3-pin signal interfaces including the ground interface are assigned with conventionally used earphone/microphone functions (one microphone input and one speaker output), while the other interface corresponding to the fourth pin is assigned with a function of microphone input for voice recognition in high noise environment. This function is made effective only when a connected audio device requires such function.

Separation of musical sources and structure from single-channel polyphonic recordings

Abstract: The thesis deals principally with the separation of pitched sources from singlechannel polyphonic musical recordings. The aim is to extract from a mixture a set of pitched instruments or sources, where each source contains a set of similarly sounding events or notes, and each note is seen as comprising partial, transient and noise content. The work also has implications for separating nonpitched or percussive sounds from recordings, and in general, for unsupervised clustering of a list of detected audio events in a recording into a meaningful set of source classes. The alignment of a symbolic score/MIDI representation with the recording constitutes a pre-processing stage. The three main areas of contribution are: firstly, the design of harmonic tracking algorithms and spectralfiltering techniques for removing harmonics from the mixture, where particular attention has been paid to the case of harmonics which are overlapping in frequency. Secondly, some studies will be presented for separating transient attacks from recordings, both when they are distinguishable from and when they are overlapping in time with other transients. This section also includes a method which proposes that the behaviours of the harmonic and noise components of a note are partially correlated. This is used to share the noise component of a mixture of pitched notes between the interfering sources. Thirdly, unsupervised clustering has been applied to the task of grouping a set of separated notes from the recording into sources, where notes belonging to the same source ideally have similar features or attributes. Issues relating to feature computation, feature selection, dimensionality and dependence on a symbolic music representation are explored. Applications of this work exist in audio spatialisation, audio restoration, music content description, effects processing and elsewhere.

Voice Activity Detection in Personal Audio Recordings Using Autocorrelogram Compensation

Abstract: This paper presents a novel method for identifying regions of speech in the kinds of energetic and highly-variable noise present in ‘personal audio’ collected by body-worn continuous recorders. Motivated by psychoacoustic evidence that pitch is crucial in the perception and organization of sound, we use a noise-robust pitch detection algorithm to locate speech-like regions. To avoid false alarms resulting from background noise with strong periodic components (such as air-conditioning), we add a new channel selection scheme to suppress frequency subbands where the autocorrelation is more stationary than encountered in voiced speech. Quantitative evaluation shows that these harmonic noises are effectively removed by this compensation technique in the domain of autocorrelogram, and that detection performance is significantly better than existing algorithms for detecting the presence of speech in real-world personal audio recordings.

Audio signal segmentation algorithm

Abstract: The present invention discloses an audio signal segmentation algorithm comprising the following steps. First, an audio signal is provided. Then, an audio activity detection (AAD) step is applied to divide the audio signal into at least one noise segment and at least one noisy audio segment. Then, an audio feature extraction step is used on the noisy audio segment to obtain multiple audio features. Then, a smoothing step is applied. Then, multiple speech frames and multiple music frames are discriminated. The speech frames and the music frames compose at least one speech segment and at least one music segment. Finally, the speech segment and the music segment are segmented from the noisy audio segment.

Analysis of Correlation between Audio and Visual Speech Features for Clean Audio Feature Prediction in Noise

Abstract: The aim of this work is to examine the correlation between audio and visual speech features. The motivation is to find visual features that can provide clean audio feature estimates which can be used for speech enhancement when the original audio signal is corrupted by noise. Two audio features (MFCCs and formants) and three visual features (active appearance model, 2-D DCT and cross-DCT) are considered with correlation measured using multiple linear regression. The correlation is then exploited through the development of a maximum a posteriori (MAP) prediction of audio features solely from the visual features. Experiments reveal that features representing broad spectral information have higher correlation to visual features than those representing finer spectral detail. The accuracy of prediction follows the results found in the correlation measurements.

Fuzzy clustering of Raman spectral imaging data with a wavelet-based noise-reduction approach.

Abstract: Raman spectral imaging has been widely used for extracting chemical information from biological specimens. One of the challenges is to cluster the chemical groups from the vast amount of hyperdimensional spectral imaging data so that functionally similar groups can be identified. In this paper, we present an approach that combines a differential wavelet-based data smoothing with a fuzzy clustering algorithm for the classification of Raman spectral images. The preprocessing of the spectral data is facilitated by decomposing them in the differential wavelet domain, where the discrimination of true spectral features and noise can be easily performed using a multi-scale pointwise product (MPP) criterion. This approach is applied to the classification of spectral data collected from adhesive/dentin interface specimens where the spectral data exhibit different signal-to-noise ratios. The proposed wavelet approach has been compared to several conventional noise-removal algorithms.

Hearing aid and a method of processing signals

Abstract: A hearing aid ( 30 ) comprises a microphone ( 71 ), a signal processing means ( 20 ) and an output transducer ( 22 ), and the signal processing means ( 20 ) comprises a set of audio processing parameters mapped to a set of stored noise classes ( 12 ) and means ( 8 ) for classifying the background noise for the purpose of optimizing the frequency response in order to minimize the effects of the background noise. The hearing aid may further comprise a neural net for controlling the frequency response. A method for reducing a noise component in a signal is also devised, which method comprises classification of the noise component, comparing the noise component to a set of known noise components, and adapting the processed audio signals according to a corresponding set of frequency response parameters.

Systems and methods for reducing audio noise

Abstract: Various embodiments of systems and methods for reducing audio noise are disclosed. One or more sound components such as noise (154, 156) and network tone (158) can be detected based on power spectrum (152) obtained from a time-domain signal (142). Results of such detection can be used to make decisions (162) in determination of an adjustment spectrum (164, 166) that can be applied to the power spectrum. The adjusted power spectrum can be transformed back into a time-domain signal (172) that substantially removes undesirable noise(s) and/or accounts for known sound components such as the network tone.

Spectral Cues for Robust Sound Localization with Pinnae

Abstract: An important ability in auditory robots is the localization of sound source. In this paper, a robust method to localize the vertical direction of the sound source with two microphones and pinnae is proposed. In order to achieve vertical sound source localization, the method of detecting spectral cues, the relationship between spectral cues and source direction are studied. In addition, this paper considers sound source separation in order to recognize and isolate spectral cues only from the sound source in order to make the method robust to extraneous noise. Furthermore the authors designed an audio servo with the proposed spectral cues and implemented the method in an actual robot. The experimental results confirmed the effectiveness of the method.

Word recognition of digit triplets and monosyllabic words in multitalker babble by listeners with sensorineural hearing loss.

Abstract: In an initial experiment (Wilson and Weakley, 2004), word recognition was assessed with six digit triplets presented at 14 signal-to-babble ratios (S/B) in 2 dB steps An abbreviated version of the protocol was developed for clinic use involving three digit triplets at 7 S/Bs in 4 dB steps The purpose of this experiment was to examine the relationship between the two digit protocols with comparisons made with other variables including age, pure-tone thresholds, subjective measures of understanding speech in quiet and in noise, and word recognition of monosyllabic words in quiet and in babble Ninety-six listeners with sensorineural hearing loss participated For equivalent performance, the short version of the digit triplets required (1) a 26 dB more favorable S/B than the long version and (2) a 151 dB less favorable S/B than the words Age, hearing loss, and subjective evaluation of the ability to understand speech in quiet and in noise were not related to performance on digits or words in multitalker babble

Adaptive β-order Generalized Spectral Subtraction for Speech Enhancement

Abstract: The performance degradation of speech communication systems in noisy environments inspired increasing research on speech enhancement and noise reduction. As a well-known single-channel noise reduction technique, spectral subtraction (SS) has widely been used for speech enhancement. However, the spectral order @b set in SS is always fixed to some constants, resulting in performance limitation to a certain degree. In this paper, we first analyze the performance of the @b-order generalized spectral subtraction (GSS) in terms of the gain function to highlight its dependence on the value of spectral order @b. A data-driven optimization scheme is then introduced to quantitatively determine the change of @b with the change of the input signal-to-noise ratio (SNR). Based on the analysis results and considering the non-uniform effect of real-world noise on speech signal, we propose an adaptive @b-order GSS in which the spectral order @b is adaptively updated according to the local SNR in each critical band frame by frame as in a sigmoid function. The performance of the proposed adaptive @b-order GSS is finally evaluated objectively by segmental SNR (SEGSNR) and log-spectral distance (LSD), and subjectively by spectrograms and mean opinion score (MOS), using comprehensive experiments in various noise conditions. Experimental results show that the proposed algorithm yields an average SEGSNR increase of 2.99dB and an average LSD reduction of 2.71dB, which are much larger improvement than that obtained with the competing SS algorithms. The superiority of the proposed algorithm is also demonstrated by the highest MOS ratings obtained from the listening tests.

Frequency Filtering for a Highly Robust Audio Fingerprinting Scheme in a Real-Noise Environment

Abstract: The noise robustness of an audio fingerprinting system is one of the most important issues in music information retrieval by the content-based audio identification technique. In a real environment, sound recordings are commonly distorted by channel and background noise. Recently, Philips published a robust and efficient audio fingerprinting system for audio identification. To extract a robust and efficient audio fingerprint, Philips applied the first derivative (differential) to the frequency-time sequence of the perceptual filter-bank energies. In practice, however, the noise robustness of Philips' audio fingerprinting scheme is still insufficient. In this paper, we introduce an extension method of the audio fingerprinting scheme for the enhancement of noise robustness. As an alternative to frequency filtering, a type of band-pass filter, instead of a high-pass filter, is used to achieve robustness to background noise in a real situation. Our experimental results show that the proposed filter improves the noise robustness in audio identification.

Classification of audio as speech or non-speech using multiple threshold values

Abstract: A portion of an audio signal is separated into multiple frames from which one or more different features are extracted. These different features are used, in combination with a set of rules, to classify the portion of the audio signal into one of multiple different classifications (for example, speech, non-speech, music, environment sound, silence, etc.). In one embodiment, these different features include one or more of line spectrum pairs (LSPs), a noise frame ratio, periodicity of particular bands, spectrum flux features, and energy distribution in one or more of the bands. The line spectrum pairs are also optionally used to segment the audio signal, identifying audio classification changes as well as speaker changes when the audio signal is speech.

Wind noise reduction method for speech recording using multiple noise templates and observed spectrum fine structure

Abstract: Wind noise affects the quality of the speech recording in the field. In this paper, we propose a wind noise reduction method based on a signal processing technique. In the method, spectrum envelopes of wind noise are estimated by using referential multiple wind noise templates and the low frequency band spectrum envelope of the observed signal. Then, we estimate the noise spectrum using the estimated spectrum envelope and the fine structure of the observed signal. Finally, we subtract this estimated noise spectrum from the observed signal. For evaluating the proposed method, we conducted subjective and objective evaluation. The experimental results showed that the proposed method achieved much better improvement than conventional spectral subtraction.

Apparatus and method of reducing noise of earphones, noise reducing earphones, and a portable audio reproducing apparatus having the same

Abstract: An apparatus and method of reducing noise in a portable audio reproducing apparatus using earphones. The apparatus includes an earphone unit having a speaker unit and a microphone to output an audio signal and to generate anti-noise with respect to external noise, and a circuit unit to compensate a frequency characteristic of the anti-noise generated by the microphone of the earphone unit, to add the anti-noise to an input audio signal, and to remove background noise using the anti-noise by outputting the audio signal having the anti-noise to the speaker unit.

System and method for noise canceling in a mobile phone headset accessory

Abstract: Disclosed is a system, method, and computer program product for canceling ambient noise in a portable mobile communications device that is coupled with a standard non-noise canceling headset assembly. The portable mobile communications device receives detected ambient noise from the headset assembly microphone and creates a noise canceling ambient noise sound wave that is 180° out of phase with the ambient noise sound wave. The noise canceling ambient noise sound wave is then combined with an intended sound wave such as music or speech. The combined noise canceling ambient noise sound wave and intended sound wave are then forwarded to the headset assembly such that the noise canceling ambient noise sound wave negates the ambient noise present at the headset assembly during playback of the intended sound wave. Noise canceling can be achieved using hardware filters or via a noise canceling software application within the portable mobile communications device.