Abstract:
According to one aspect of the present invention, a method and apparatus is provided in which input data (e.g., input video data) is encoded in accordance with a first coding standard (e.g., MPEG-4) to generate encoded data. The input data is also encoded based on a reconstruction of the input data to generate encoded side information associated with the input data. The encoded data are transmitted to a destination (e.g., a decoding subsystem) over a first channel and the encoded side information are transmitted to the destination over a second channel. The encoded data and the encoded side information are decoded and combined at the destination to generate output data.
Abstract:
A method and system that improves voice recognition by improving storage of voice recognition (VR) templates. The improved storage means that more VR models can be stored in memory. The more VR models that are stored in memory, the more robust the VR system and therefore the more accurate the VR system. Lossy compression techniques are used to compress VR models. In one embodiment, A-law compression and A-law expansion are used to compress and expand VR models. In another embodiment, Mu-law compression and Mu-law expansion are used to compress and expand VR models. VR models are compressed during a training process and they are expanded during voice recognition.
Abstract:
A novel and improved method and an accompanying apparatus provide for a distributed voice recognition (VR) capability in a remote device (201). Remote device (201) decides and controls what portions of the VR processing may take place at remote device (201) and what other portions may take place at a base station (202) in wireless communication with remote device (201).
Abstract:
A method of using spiking neural network delays to represent sequences includes assigning one or more symbol neurons to each symbol in a dictionary. The method also includes assigning a synapse from each symbol neuron in a group to a particular ngram neuron. A set of synapses associated with the group of symbol neurons comprises a bundle of synapses. In addition, the method includes assigning a delay to each synapse in the bundle. The method further includes representing a symbol sequence based on sequential spiking of symbol neurons and ngram neuron spikes in response to detecting inter event intervals.
Abstract:
Certain aspects of the present disclosure relate to techniques for measuring body impedance based on baseband signal detection in analog domain. Proposed methods and apparatus are able to measure an impedance of human body based on sub-Nyquist sampling of signals. The proposed techniques can be particularly beneficial for reducing overall sensor power when an actuation signal generates electrical signals corresponding to vital signs in humans.
Abstract:
Certain aspects of the present disclosure relate to a method for compressed sensing (CS). The CS is a signal processing concept wherein significantly fewer sensor measurements than that suggested by Shannon/Nyquist sampling theorem can be used to recover signals with arbitrarily fine resolution. In this disclosure, the CS framework is applied for sensor signal processing in order to support low power robust sensors and reliable communication in Body Area Networks (BANs) for healthcare and fitness applications.
Abstract:
Techniques for efficiently performing full and scaled transforms on data received via full and scaled interfaces, respectively, are described. A full transform is a transform that implements the complete mathematical description of the transform. A full transform operates on or provides full transform coefficients. A scaled transform is a transform that operates on or provides scaled transform coefficients, which are scaled versions of the full transform coefficients. The scaled transform may have lower computational complexity whereas the full transform may be simpler to use by applications. The full and scaled transforms may be for a 2D IDCT, which may be implemented in a separable manner with 1D IDCTs. The full and scaled transforms may also be for a 2D DCT, which may be implemented in a separable manner with 1D DCTs. The 1D IDCTs and 1D DCTs may be implemented in a computationally efficient manner.
Abstract:
A method and system that improves voice recognition in a distributed voice recognition system. A distributed voice recognition system 50 includes a local VR engine 52 in a subscriber unit 54 and a server VR engine 56 on a server 58. When the local VR engine 52 does not recognize a speeh segment segment to the local VR engine 56 downloads information corresponding the speech segment to the local VR engine 52. The local VR engine 52 may combine its speech segement information with downloaded information to create resultant information for a speech segment. The local VR engine 52 may also apply a function to downloaded information to create resultant information for a speech segment. The local VR engine 52 may also apply a function to downloaded information to create resultant information. Resultant information then may be uploaded from the local VR engine 52 to the server VR engine 56.
Abstract:
This disclosure describes techniques that can facilitate multimedia telephony. In one example, a method for communication of multimedia data comprises determining a first level of throughput associated with multimedia data communication from a first access terminal to a network, determining a second level of throughput associated with multimedia data communication from the network to a second access terminal based on feedback from the second access terminal to the first access terminal via the network, determining a budget associated with communication of a video unit of the multimedia data, and coding the video unit of the multimedia data based on the budget and the first and second levels of throughput.
Abstract:
A method and system for resynchronizing an embedded multimedia system using bytes consumed in an audio decoder. The bytes consumed provides a mechanism to compensate for bit error handling and correction in a system that does not require re-transmission. The audio decoder keeps track of the bytes consumed and periodically reports the bytes consumed. A host microprocessor indexes the actual bytes consumed since bit errors may have been handled or corrected to a predetermined byte count to determine whether resynchronization is necessary.