Abstract: A method for reducing a computational complexity of an m-stage adaptive filter is provided by expanding a weighted sum of forward prediction error squares into a corresponding binomial expansion series, expanding a weighted sum of backward prediction error squares into a corresponding binomial expansion series, and determining coefficient updates of the adaptive filter with the weighted sums of forward and backward prediction error squares approximated by a select number of terms of their corresponding binomial expansion series.

Abstract: A hands-free circuit (10) and method produces audio information (90) corresponding to voice tag information (60) stored either in the hands-free circuit (10) or in a wireless device (320). The hands-free circuit includes a wireless local area network (WLAN) transceiver (20), memory (40) and a speech processor (30). For example, the wireless local area network transceiver (20) may be a Bluetooth transceiver that communicates with the wireless device (320) and receives wireless device information (80). The wireless device information (80) may represent caller identification information, call processing information relating to the status of a call, phone status information or any suitable information. The speech processor (30) produces audio information (90) corresponding to the voice tag information (60). According to one embodiment, the speech processor (30) produces speech synthesized wireless device information (80), in-band ring tone information or any suitable information.

Abstract: A method of providing information storage by means of Automatic Speech Recognition through a communication device of a vehicle comprises establishing a voice communication between an external source and a user of the vehicle, receiving information from the external source, processing the received information using an Automatic Speech Recognition unit in the vehicle and storing the recognized speech in textual form for future retrieval or use.

Abstract: A wireless unit or hub for a vehicle includes a wireless communication interface, such as a Bluetooth® interface. The hub stores profiles for wireless devices that can actively interact with the hub. The wireless devices, which can be cellular phones, headsets, portable music players, and Personal Digital Assistants, are capable of providing audio data, visual data, or both to the hub. The hub monitors for wireless devices in a personal area network of the hub. Based on the profiles, the hub establishes wireless connections with the wireless devices. Using an arbitration scheme, the hub controls the delivery of audio and/or visual data provided by the wireless devices to one or more modules communicatively coupled to the hub. The modules, which can be a user interface module, audio module, visual modules, navigation system, and vehicle entertainment system, are capable of delivering audio, visual, or audio-visual data in the vehicle.

Abstract: An apparatus and method for enhancing a handheld communication device via a telematics system in a vehicle is disclosed. Audio received at the handheld device is transferred to the telematics system in the vehicle. The received audio is then analyzed to determine whether it contains speech, and if so, an audio present signal is generated and the received audio is recorded into a memory coupled to the telematics system. The user can then engage the user interface of the telematics system to replay the recorded audio. Bluetooth protocol is preferably used to establish a channel between the handheld device and the telematics system, which can occur automatically when the two are in proximity. Analysis of the received audio preferably comprises use of a voice detector as part of a speech recognition system otherwise used by the telematics system to assess spoken commands.

Abstract: A method for reducing a computational complexity of an m-stage adaptive filter is provided by expanding a weighted sum of forward prediction error squares into a corresponding binomial expansion series, expanding a weighted sum of backward prediction error squares into a corresponding binomial expansion series, and determining coefficient updates of the adaptive filter with the weighted sums of forward and backward prediction error squares approximated by a select number of terms of their corresponding binomial expansion series.

Abstract: A method and apparatus for adapting a help menu on a user interface, utilizing an input method such as a speech recognition system, for increased efficiency. A list of menu items is presented on the user interface including an optional menu item to reinstate any previously removed menu items. A user selects an item from the menu, such as a help menu, which can then be removed from the list of menu items in accordance with predetermined criteria. The criteria can include how many times the menu item has been accessed and when. In this way, help menu items that are familiar to a user are removed to provide an abbreviated help menu which is more efficient and less frustrating to a user, particularly in a busy and distracting environment such as a vehicle.

Abstract: A method and apparatus for assisting a user in the dialing of a telephone call using voice nametags. A first step includes inputting a telephone number with text. The next steps automatically create a voice nametag from the text for each telephone number using grapheme-to-phoneme conversion. Upon initiation of dialing, a next step enters a spoken phrase, which is then compared to the stored voice nametags. A next step determines a confidence level score of a match between the spoken phrase data and the representations of the stored voice nametags against at least one threshold. A next step selects the stored voice nametag with the best match to the spoken phrase data. A next step provides feedback to the user dependent upon the confidence level of the match, which can include automatically dialing the call if the confidence level is high enough. As part of this last step, an audio feedback tag is generated and stored based on the recognition result passing a confidence threshold criterion.

Abstract: A hands-free circuit (10) and method produces audio information (90) corresponding to voice tag information (60) stored either in the hands-free circuit (10) or in a wireless device (320). The hands-free circuit includes a wireless local area network (WLAN) transceiver (20), memory (40) and a speech processor (30). For example, the wireless local area network transceiver (20) may be a Bluetooth transceiver that communicates with the wireless device (320) and receives wireless device information (80). The wireless device information (80) may represent caller identification information, call processing information relating to the status of a call, phone status information or any suitable information. The speech processor (30) produces audio information (90) corresponding to the voice tag information (60). According to one embodiment, the speech processor (30) produces speech synthesized wireless device information (80), in-band ring tone information or any suitable information.

Abstract: An echo canceler circuit (200) and method performs cascaded echo cancellation and noise suppression in a non-interfering manner. The echo canceler circuit (200) includes pre-noise suppression logic (210), echo canceler coefficient logic (218), noise suppression logic (212) and an echo canceler filter (216). The pre-noise suppression logic (210) receives pre-echo canceler uplink data (64) and downlink data (52), and in response produces pre-noise suppression uplink data (224). The echo canceler coefficient logic(218) receives the pre-noise suppression uplink data (224) and the pre-echo canceler uplink data (64), and in response produces filter coefficient data (226). The noise suppression logic (212) receives the pre-noise suppression uplink data (224), and in response produces noise suppressed uplink data (228). The echo canceler filter (216) receives the noise suppressed uplink data (228) and the filter coefficient data (226) and in response produces final uplink data (230).

Abstract: A downlink activity and double talk probability detector and method for an echo canceler circuit (10) improves the stability of an echo canceler adaptive filter (300) and improves the attenuation of post-echo canceler uplink data (388). The echo canceler circuit (10) includes a downlink activity and double talk probability data generator (30) and an echo canceler stage (20). The downlink activity and double talk probability data generator (30) receives pre-echo canceler uplink data (40) and downlink data (50) and in response produces double talk probability data (60) and downlink activity data (70). The echo canceler stage (20) receives the downlink data (50), the pre-echo canceler uplink data (40), the double talk probability data (60) and the downlink activity data (70), and in response produces uplink data (80).

Abstract: Method of controlling a communications session (101) can include a handset (102) determining one of a docked condition (150) and an undocked condition (152). A communications session (101) is initiated where the communications session spans from the handset (102) to a remote communications device (104) using a WPAN communications link (110), and out from the remote communications device (104) using a cellular link (112). The handset (102) can translate between the WPAN communications link (110) and the cellular link (112). If the handset (102) is in the docked condition (150), the handset (102) can route an audio component (153) through the docking station (106). If the handset (102) is in the undocked condition (152), the handset (102) can route the audio component (155) through the handset (102).