1. Technical Field
This disclosure relates to a communications protocol, and more particularly to a protocol that transports control, configuration, and/or monitoring data used in a speech enhancement system in a vehicle.
2. Related Art
Vehicles may include wireless communication systems. A user may communicate with the wireless communication system through a hard-wired interface or through a wireless interface, which may include a hands-free headset. Such wireless communication systems may include or may be coupled to a noise reduction system. The noise reduction system may include a plurality of noise reduction modules to handle the various acoustic artifacts.
To optimize the noise reduction system, a technician may manually adjust the noise reduction system based on the specific acoustic chamber corresponding to the vehicle or vehicle model. Adjusting the noise reduction system by depressing buttons and indicators on the head-end or noise reduction system may be time consuming and expensive. Once the noise reduction system has been initialized, activating and/or deactivating individual modules may require rebooting of the system, which may be time consuming.
A remote control server protocol system transports data to a client system. The client system communicates with the server application using a platform-independent communications protocol. The client system sends commands and audio data to the server application. The server application may respond by transmitting audio and other messages to the client system. The messages may be transmitted over a single communications channel.
Other systems, methods, features, and advantages will be, or will become, apparent to one with skill in the art upon examination of the following figures, and detailed description. It is intended that all such additional systems, methods, features and advantages be included within this description, be within the scope of the invention, and be protected by the following claims.
The system may be better understood with reference to the following drawings and description. The components in the figures are not necessarily to scale, emphasis instead being placed upon illustrating the principles of the invention. Moreover, in the figures, like-referenced numerals designate corresponding parts throughout the different views.
The system provides platform and transport independent methods for transferring character and embedded data (e.g., binary data). It allows for the same interface to be used for monitoring multiple channels of audio data and sending and receiving configuration and control parameters. The protocol may handle sending signals to trigger application events in speech signal enhancement systems.
The client system 110 may be a portable computer, such as laptop computer, terminal, wireless interface, or other device used by a technician or user to adjust, tune, or modify the speech enhancement system 116. The client system 110 may be separate and independent from the speech enhancement system 116, and may run under a Windows® operating system. Other operating systems and/or computing platforms may also be used.
The application-to-client environment 106 may provide a platform and transport independent system for transferring commands, messages, and data, such as character data, embedded data, binary data, audio streams, and other data, between the client system 110 and the speech enhancement system 116 by using a remote control server (RCS) protocol 202. The RCS protocol 202 may be a communications protocol that may transport control data, configuration data and/or for monitoring data between the speech enhancement system 116 and the client system 110. Data may be sent over a single or common interface or channel. The RCS protocol 202 may permit a user to efficiently tune and adjust the speech enhancement system 116 in the vehicle for optimum performance through the client system 110. Because the acoustic “chamber” may differ from vehicle to vehicle and from vehicle model to vehicle model, a user may tune and adjust the parameters of the speech enhancement system 116 for each specific acoustic environment loudly or remotely.
The client system 110 may include an RCS protocol client application 210, which may comprise a software “plug-in.” The RCS protocol client application 210 may translate commands issued by the client system 110 under user control into an RCS protocol format 202. The speech enhancement system 116 may include a corresponding RCS protocol server application 220, which may comprise a software “plug-in.” The RCS protocol server application 220 may translate data and commands received from the client system 110 in an RCS protocol format 202 into control commands and data, which may be processed by the speech enhancement system 116. By using the software 210 and 220, communication may occur independent of the platform.
In some systems, the processing modules 304 may comprise a collection of routines and data structures that perform tasks, and may be stored in a library of software programs. The processing module may include an interface that recognizes data types, variables and routines in an implementation accessible only to the module. The processing modules may be accessed to process a stream of audio data received from or sent to the wireless communication device 120. Any of the processing modules 304 may process the audio data during operation of the speech enhancement system 116. The speech enhancement system 116 may process a stream of audio data on a frame-by-frame basis. A frame of audio data may include, for example, 128 samples of audio data. Other frame lengths may be used. Each sample in a frame may represent audio data digitized at a basic sample rate of about 8 KHz or about 16 KHz, for example.
The processing modules 304 may be “created” or generated during initialization of the speech enhancement system 116 or during normal operation of the speech enhancement system that may be under control of the client system 110. During the generation process 304, memory may be mapped, allocated, and configured for some or all of the modules, and various parameters may be set. The processing modules 304 may be uninstalled during initialization or during normal operation of the speech enhancement system 116 under the control of the client system 110.
Each processing module 304 or software process (or hardware) that performs the speech enhancement processing may be accessed and copied from a library of speech enhancement processes into memory. The speech enhancement system 116 may include processing modules, such as an echo-cancellation module 310, a noise reduction module 312, an automatic gain control module 314, a parametric equalization module 316, a high-frequency encoding module 318, a wind buffet removal module 320, a dynamic limiter module 322, a complex mixer module 324, a noise compensation module 326, and a bandwidth extension module 328. For example, a signal enhancement module may be included, which may be described in application Ser. Nos. 10/973,575, 11/757,768, and 11/849,009, which are incorporated by reference. Such processing modules may process data on the receive side or the transmit side. A diagnostic support module 340 may be included to facilitate debugging of the speech enhancement system 116. Other noise reduction or speech enhancement modules 304 may be included. The speech enhancement system 116 may be a compiled and linked library of processing modules available from Harman International of California under the name of Aviage Acoustic Processing System.
The speech enhancement system 116 may include a processor 450 or other computing device, memory 456, disk storage 458, a communication interface 460, and other hardware 462 and software components. The processor 450 may communicate with various signal processing components, such as filters, mixers, limiters, attenuators, and tuners, which may be implemented in hardware or software or a combination of hardware and software. Such signal processing components may be part of the speech enhancement system 116 or may be separate from the speech enhancement system. The client system 110 or portable computer may also include a processor 470 or other computing device, memory 472, disk storage 474, a communication interface 476, and other hardware and software components.
The processing modules 304 may process the audio data from the wireless communication device 120 serially or in a parallel manner (Act 530). The processor 450 may periodically determine if a request (message and/or command) has been received from the client system 110 (Act 540). In some systems, the client request may request service from the processor 450.
When a request is received from the client system 110, the processor 450 may call the RCS protocol server application 220 to translate an RCS protocol message received from the client system 110 (Act 544). The RCS protocol server application 220 may be an API (application programming interface) program. The API 220 may recognize the commands, instructions, and data provided in RCS protocol format and may translate such information into signals recognized by the speech enhancement system 116. The processor 450 may execute a process (Act 550) specified by the client system 110. If a terminate signal is detected (Act 560), the link between the client system and the application may be terminated. If no terminate signal is received, processing by the processing modules 304 may continue (Act 530).
A response (“rset” 646) sent by the application 116 in response to the message sent by the client system 110 may include attributes 650 returned by the message call. An “error” parameter 656 may contain a code 658 indicating that an error has occurred or that no error has occurred. A “no error” indication means that the “set” message was received correctly. The types of information described above may apply to each of the messages described in
The SET message 600 may be used to set or define parameters or variables in the processing modules 304. For example, a noise reduction floor, which may be a parameter in the noise reduction module 312, may be set to 10 dB using this message. A character string “noise reduction floor” may be entered into a “param” field 662 to identify the parameter to be set, and the value of 10 may be entered into a “data” field 664.
In some systems, the processing modules 304 may be created and/or destroyed individually by the appropriate commands sent by the client system 110. It is not necessary that memory for all of the processes be created or destroyed at one time.
The logic, circuitry, and processing described above may be encoded in a computer-readable medium such as a CDROM, disk, flash memory, RAM or ROM, an electromagnetic signal, or other machine-readable medium as instructions for execution by a processor. Alternatively or additionally, the logic may be implemented as analog or digital logic using hardware, such as one or more integrated circuits (including amplifiers, adders, delays, and filters), or one or more processors executing amplification, adding, delaying, and filtering instructions; or in software in an application programming interface (API) or in a Dynamic Link Library (DLL), functions available in a shared memory or defined as local or remote procedure calls; or as a combination of hardware and software.
The logic may be represented in (e.g., stored on or in) a computer-readable medium, machine-readable medium, propagated-signal medium, and/or signal-bearing medium. The media may comprise any device that contains, stores, communicates, propagates, or transports executable instructions for use by or in connection with an instruction executable system, apparatus, or device. The machine-readable medium may selectively be, but is not limited to, an electronic, magnetic, optical, electromagnetic, or infrared signal or a semiconductor system, apparatus, device, or propagation medium. A non-exhaustive list of examples of a machine-readable medium includes: a magnetic or optical disk, a volatile memory such as a Random Access Memory “RAM,” a Read-Only Memory “ROM,” an Erasable Programmable Read-Only Memory (i.e., EPROM) or Flash memory, or an optical fiber. A machine-readable medium may also include a tangible medium upon which executable instructions are printed, as the logic may be electronically stored as an image or in another format (e.g., through an optical scan), then compiled, and/or interpreted or otherwise processed. The processed medium may then be stored in a computer and/or machine memory.
The systems may include additional or different logic and may be implemented in many different ways. A controller may be implemented as a microprocessor, microcontroller, application specific integrated circuit (ASIC), discrete logic, or a combination of other types of circuits or logic. Similarly, memories may be DRAM, SRAM, Flash, or other types of memory. Parameters (e.g., conditions and thresholds) and other data structures may be separately stored and managed, may be incorporated into a single memory or database, or may be logically and physically organized in many different ways. Programs and instruction sets may be parts of a single program, separate programs, or distributed across several memories and processors. The systems may be included in a wide variety of electronic devices, including a cellular phone, a headset, a hands-free set, a speakerphone, communication interface, or an infotainment system.
While various embodiments of the invention have been described, it will be apparent to those of ordinary skill in the art that many more embodiments and implementations are possible within the scope of the invention. Accordingly, the invention is not to be restricted except in light of the attached claims and their equivalents.
This application claims the benefit of priority from U.S. Provisional Application Ser. No. 60/973,131, filed Sep. 17, 2007, which is incorporated by reference.
Number | Name | Date | Kind |
---|---|---|---|
4238746 | McCool et al. | Dec 1980 | A |
4282405 | Taguchi | Aug 1981 | A |
4486900 | Cox et al. | Dec 1984 | A |
4531228 | Noso et al. | Jul 1985 | A |
4628156 | Irvin | Dec 1986 | A |
4630305 | Borth et al. | Dec 1986 | A |
4731846 | Secrest et al. | Mar 1988 | A |
4791390 | Harris et al. | Dec 1988 | A |
4811404 | Vilmur et al. | Mar 1989 | A |
4843562 | Kenyon et al. | Jun 1989 | A |
4939685 | Feintuch | Jul 1990 | A |
4969192 | Chen et al. | Nov 1990 | A |
5027410 | Williamson et al. | Jun 1991 | A |
5056150 | Yu et al. | Oct 1991 | A |
5146539 | Doddington et al. | Sep 1992 | A |
5278780 | Eguchi et al. | Jan 1994 | A |
5313555 | Kamiya | May 1994 | A |
5377276 | Terai et al. | Dec 1994 | A |
5400409 | Linhard | Mar 1995 | A |
5406622 | Silverberg et al. | Apr 1995 | A |
5412735 | Engebretson et al. | May 1995 | A |
5432859 | Yang et al. | Jul 1995 | A |
5473702 | Yoshida et al. | Dec 1995 | A |
5479517 | Linhard | Dec 1995 | A |
5494886 | Kehne et al. | Feb 1996 | A |
5495415 | Ribbens et al. | Feb 1996 | A |
5502688 | Recchione et al. | Mar 1996 | A |
5526466 | Takizawa | Jun 1996 | A |
5568559 | Makino | Oct 1996 | A |
5572262 | Ghosh | Nov 1996 | A |
5584295 | Muller et al. | Dec 1996 | A |
5590241 | Park et al. | Dec 1996 | A |
5615298 | Chen | Mar 1997 | A |
5617508 | Reaves | Apr 1997 | A |
5641931 | Ogai et al. | Jun 1997 | A |
5677987 | Seki et al. | Oct 1997 | A |
5680508 | Liu | Oct 1997 | A |
5692104 | Chow et al. | Nov 1997 | A |
5701344 | Wakui | Dec 1997 | A |
5714997 | Anderson | Feb 1998 | A |
5742694 | Eatwell | Apr 1998 | A |
5819215 | Dobson et al. | Oct 1998 | A |
5845243 | Smart et al. | Dec 1998 | A |
5920840 | Satyamurti et al. | Jul 1999 | A |
5920848 | Schutzer et al. | Jul 1999 | A |
5933801 | Fink et al. | Aug 1999 | A |
5949886 | Nevins et al. | Sep 1999 | A |
5949888 | Gupta et al. | Sep 1999 | A |
5953694 | Pillekamp | Sep 1999 | A |
6011853 | Koski et al. | Jan 2000 | A |
6084907 | Nagano et al. | Jul 2000 | A |
6111957 | Thomasson | Aug 2000 | A |
6144336 | Preston et al. | Nov 2000 | A |
6163608 | Romesburg et al. | Dec 2000 | A |
6167375 | Miseki et al. | Dec 2000 | A |
6173074 | Russo | Jan 2001 | B1 |
6175602 | Gustafsson et al. | Jan 2001 | B1 |
6192134 | White et al. | Feb 2001 | B1 |
6199035 | Lakaniemi et al. | Mar 2001 | B1 |
6219418 | Eriksson et al. | Apr 2001 | B1 |
6249275 | Kodama | Jun 2001 | B1 |
6282430 | Young | Aug 2001 | B1 |
6405168 | Bayya et al. | Jun 2002 | B1 |
6408273 | Quagliaro et al. | Jun 2002 | B1 |
6434246 | Kates et al. | Aug 2002 | B1 |
6473409 | Malvar | Oct 2002 | B1 |
6493338 | Preston et al. | Dec 2002 | B1 |
6507814 | Gao | Jan 2003 | B1 |
6587816 | Chazan et al. | Jul 2003 | B1 |
6628781 | Grundström et al. | Sep 2003 | B1 |
6633894 | Cole | Oct 2003 | B1 |
6643619 | Linhard et al. | Nov 2003 | B1 |
6687669 | Schrögmeier et al. | Feb 2004 | B1 |
6690681 | Preston et al. | Feb 2004 | B1 |
6725190 | Chazan et al. | Apr 2004 | B1 |
6771629 | Preston et al. | Aug 2004 | B1 |
6782363 | Lee et al. | Aug 2004 | B2 |
6804640 | Weintraub et al. | Oct 2004 | B1 |
6822507 | Buchele | Nov 2004 | B2 |
6836761 | Kawashima et al. | Dec 2004 | B1 |
6859420 | Coney et al. | Feb 2005 | B1 |
6871176 | Choi et al. | Mar 2005 | B2 |
6891809 | Ciccone et al. | May 2005 | B1 |
6898293 | Kaulberg | May 2005 | B2 |
6910011 | Zakarauskas | Jun 2005 | B1 |
6937978 | Liu | Aug 2005 | B2 |
7020291 | Buck et al. | Mar 2006 | B2 |
7026957 | Rubenstein | Apr 2006 | B2 |
7117149 | Zakarauskas | Oct 2006 | B1 |
7146012 | Belt et al. | Dec 2006 | B1 |
7146316 | Alves | Dec 2006 | B2 |
7167516 | He | Jan 2007 | B1 |
7167568 | Malvar et al. | Jan 2007 | B2 |
7206418 | Yang et al. | Apr 2007 | B2 |
7231347 | Zakarauskas | Jun 2007 | B2 |
7269188 | Smith | Sep 2007 | B2 |
7272566 | Vinton | Sep 2007 | B2 |
7302390 | Yang et al. | Nov 2007 | B2 |
7613532 | Anderson et al. | Nov 2009 | B2 |
7653543 | Blair et al. | Jan 2010 | B1 |
8005668 | Arun | Aug 2011 | B2 |
20010005822 | Fujii et al. | Jun 2001 | A1 |
20010028713 | Walker | Oct 2001 | A1 |
20020052736 | Kim et al. | May 2002 | A1 |
20020071573 | Finn | Jun 2002 | A1 |
20020176589 | Buck et al. | Nov 2002 | A1 |
20030040908 | Yang et al. | Feb 2003 | A1 |
20030093265 | Xu et al. | May 2003 | A1 |
20030093270 | Domer | May 2003 | A1 |
20030097257 | Amada et al. | May 2003 | A1 |
20030101048 | Liu | May 2003 | A1 |
20030206640 | Malvar et al. | Nov 2003 | A1 |
20030216907 | Thomas | Nov 2003 | A1 |
20040002856 | Bhaskar et al. | Jan 2004 | A1 |
20040002858 | Attias et al. | Jan 2004 | A1 |
20040024600 | Hamza et al. | Feb 2004 | A1 |
20040071284 | Abutalebi et al. | Apr 2004 | A1 |
20040078200 | Alves | Apr 2004 | A1 |
20040138882 | Miyazawa | Jul 2004 | A1 |
20040165736 | Hetherington et al. | Aug 2004 | A1 |
20040167777 | Hetherington et al. | Aug 2004 | A1 |
20040179610 | Lu et al. | Sep 2004 | A1 |
20050075866 | Widrow | Apr 2005 | A1 |
20050114128 | Hetherington et al. | May 2005 | A1 |
20050240401 | Ebenezer | Oct 2005 | A1 |
20060034447 | Alves et al. | Feb 2006 | A1 |
20060056502 | Callicotte | Mar 2006 | A1 |
20060074646 | Alves et al. | Apr 2006 | A1 |
20060089958 | Giesbrecht et al. | Apr 2006 | A1 |
20060089959 | Nongpiur et al. | Apr 2006 | A1 |
20060100868 | Hetherington et al. | May 2006 | A1 |
20060115095 | Giesbrecht et al. | Jun 2006 | A1 |
20060116873 | Hetherington et al. | Jun 2006 | A1 |
20060251268 | Hetherington et al. | Nov 2006 | A1 |
20060287859 | Hetherington et al. | Dec 2006 | A1 |
20070033031 | Zakarauskas | Feb 2007 | A1 |
20070088544 | Acero et al. | Apr 2007 | A1 |
20070136055 | Hetherington | Jun 2007 | A1 |
20080010057 | Chengalvarayan et al. | Jan 2008 | A1 |
20080300025 | Song et al. | Dec 2008 | A1 |
20090119088 | Ferris | May 2009 | A1 |
20090146848 | Ghassabian | Jun 2009 | A1 |
20110131045 | Cristo et al. | Jun 2011 | A1 |
Number | Date | Country |
---|---|---|
2158847 | Sep 1994 | CA |
2157496 | Oct 1994 | CA |
2158064 | Oct 1994 | CA |
0 076 687 | Apr 1983 | EP |
0 275 416 | Jul 1988 | EP |
0 558 312 | Sep 1993 | EP |
0 629 996 | Dec 1994 | EP |
0 629 996 | Dec 1994 | EP |
0 750 291 | Dec 1996 | EP |
0 948 237 | Oct 1999 | EP |
1 450 353 | Aug 2004 | EP |
1 450 354 | Aug 2004 | EP |
1 669 983 | Jun 2006 | EP |
06269084 | Sep 1994 | JP |
06319193 | Nov 1994 | JP |
WO 0041169 | Jul 2000 | WO |
WO 0156255 | Aug 2001 | WO |
WO 0173761 | Oct 2001 | WO |
WO 2006130668 | Dec 2006 | WO |
Entry |
---|
Anderson C.M., et al: “Adaptive Enhancement of Finite Bandwidth Signals in White Gaussian Noise,” IEEE Trans. On Acoustics, Speech and Signal Processing, vol. ASSP-31, No. 1, Feb. 1983, pp. 17-28. |
Avendano, C. et al., “Study on the Dereverberation of Speech Based on Temporal Envelope Filtering,” Proc. ICSLP '96, Oct. 1996, pp. 889-892. |
Berk et al., “Data Analysis with Microsoft Excel,” Duxbury Press, 1998, pp. 236-239 and 256-259. |
Bilcu, R.C. et al., “A New Variable Length LMS Algorithm: Theoretical Analysis and Implementations,” 2002, IEEE, pp. 1031-1034. |
Byun K.J., et al: “Noise Whitening-Based Pitch Detection for Speech Highly Corrupted by Colored Noise,” ETRI Journal, vol. 25, No. 1, Feb. 2003, pp. 49-51. |
Campbell D.A., et al: “Dynamic Weight Leakage for LMS Adaptive Linear Predictors,” Tencon '96 Proceedings, 1996 IEEE Tencon Digital Signal Processing Applications Perth, WA, Australia Nov. 26-29, 1996, NY, NY, USA, IEEE, US, vol. 2, Nov. 26, 1996, pp. 574-579. |
Chang J.H., et al: “Pitch Estimation of Speech Signal Based on Adaptive Lattice Notch Filter,” Signal Processing, Elsevier Science Publishers B.V. Amsterdam, NL, vol. 85, No. 3, Mar. 2005, pp. 637-641. |
Fiori, S. et al., “Blind Deconvolution by Modified Bussgang Algorithm,” Dept. of Electronics and Automatics—University of Ancona (Italy), ISCAS 1999, 4 pages. |
Kang, Hae-Dong; “Voice Enhancement Using a Single Input Adaptive Noise Elimination Technique Having a Recursive Time-Delay Estimator,” Kyungbook National University (Korea), Doctoral Thesis, Dec. 31, 1993, pp. 11-26. |
Kauppinen, I., “Methods for Detecting Impulsive Noise in Speech and Audio Signals,” 2002, IEEE, pp. 967-970. |
Koike, S., “Adaptive Threshold Nonlinear Algorithm for Adaptive Filters with Robustness Against Impulse Noise,” 1996, IEEE, NEC Corporation, Tokyo 108-01, pp. 1644-1647. |
Learned, R.E. et al., A Wavelet Packet Approach to Transient Signal Classification, Applied and Computational Harmonic Analysis, 1995, pp. 265-278. |
Nakatani, T., Miyoshi, M., and Kinoshita, K., “Implementation and Effects of Single Channel Dereverberation Based on the Harmonic Structure of Speech,” Proc. of IWAENC—2003, Sep. 2003, pp. 91-94. |
Nascimento, V.H., “Improving the Initial Convergence of Adaptive Filters: Variable-Length LMS Algorithms,” 2002 IEEE, pp. 667-670. |
Pornimitkul, P. et al., 2102797 Statistic Digital Signal Processing, Comparison of NLMS and RLS for Acoustic Echo Cancellation (AEC) and White Gaussian Noise (WGN), Department of Electrical Engineering Faculty of Engineering, Chulalongkorn University, 2002, pp. 1-19. |
Puder, H. et al., “Improved Noise Reduction for Hands-Free Car Phones Utilizing Information on a Vehicle and Engine Speeds,” Signal Theory, Darmstadt University of Technology, 2000, pp. 1851-1854. |
Quatieri, T.F. et al., “Noise Reduction Using a Soft-Decision Sine-Wave Vector Quantizer,” International Conference on Acoustics, Speech & Signal Processing, 1990, pp. 821-824. |
Quelavoine, R. et al., “Transients Recognition in Underwater Acoustic with Multilayer Neural Networks,” Engineering Benefits from Neural Networks, Proceedings of the International Conference EANN 1998, Gibraltar, Jun. 10-12, 1998 pp. 330-333. |
Rabiner L.R., et al: “A Comparative Performance Study of Several Pitch Detection Algorithms,” IEEE Trans. On Acoustics, Speech and Signal Processing, vol. ASSP-24, No. 5, Oct. 1976, pp. 399-418. |
Sasaoka N, et al: “A New Noise Reduction System Based on ALE and Noise Reconstruction Filter,” Circuits and Systems, 2005. ISCAS 2005. IEEE International Symposium on Kobe, Japan May 23-26, 2005, Piscataway, NJ USA, IEEE May 23, 2005, pp. 272-275. |
Seely, S., “An Introduction to Engineering Systems,” Pergamon Press Inc., 1972, pp. 7-10. |
Shust, M.R. et al., “Electronic Removal of Outdoor Microphone Wind Noise,” obtained from the Internet on Oct. 5, 2006 at: <http://www.acoustics.org/press/136th/mshust.htm>, 6 pages. |
Shust, M.R., Abstract of “Active Removal of Wind Noise From Outdoor Microphones Using Local Velocity Measurements,” J. Acoust. Soc. Am., vol. 104, No. 3, Pt 2, 1998, 1 page. |
Simon, G., “Detection of Harmonic Burst Signals,” International Journal Circuit Theory and Applications, Jul. 1985, vol. 13, No. 3, pp. 195-201. |
Tam, K. et al., “Highly Oversampled Subband Adaptive Filters for Noise Cancellation on a Low-resource DSP System,” Proc. Of Int. Conf. on Spoken Language Processing (ICSLP), Sep. 2002, pp. 1-4. |
Vaseghi, S. et al., “The Effects of Non-Stationary Signal Characteristics on the Performance of Adaptive Audio Restoration System,” 1989, IEEE, pp. 377-380. |
Vieira, J., “Automatic Estimation of Reverberation Time,” Audio Engineering Society, Convention Paper 6107, 116th Convention, May 8-11, 2004, Berlin, Germany, pp. 1-7. |
Wahab A. et al., “Intelligent Dashboard With Speech Enhancement,” Information, Communications, and Signal Processing, 1997. ICICS, Proceedings of 1997 International Conference on Singapore, Sep. 9-12, 1997, New York, NY, USA, IEEE, pp. 993-997. |
Widrow, B. et al., “Adaptive Noise Cancelling: Principles and Applications,” 1975, IEEE, vol. 63, No. 13, New York, pp. 1692-1716. |
Zakarauskas, P., “Detection and Localization of Nondeterministic Transients in Time series and Application to Ice-Cracking Sound,” Digital Signal Processing, 1993, vol. 3, No. 1, pp. 36-45. |
Number | Date | Country | |
---|---|---|---|
20090076824 A1 | Mar 2009 | US |
Number | Date | Country | |
---|---|---|---|
60973131 | Sep 2007 | US |