Abstract: A data storage device with flash memory and a flash memory control method are disclosed, which upload the physical-to-logical address mapping information of one block to the flash memory section by section. A microcontroller is configured to allocate a flash memory to provide a first run-time write block. Between a first write operation and a second write operation of the first run-time write block, the microcontroller updates a logical-to-physical address mapping table in accordance with just part of a first physical-to-logical address mapping table. The logical-to-physical address mapping table is provided within the flash memory. The first physical-to-logical address mapping table is established in the random access memory to record logical addresses corresponding to physical addresses of one block.

Abstract: According to one embodiment, an apparatus for extracting keywords from a single document includes a key sentence extraction unit and a keyword extraction unit. The key sentence extraction unit extracts key sentences from the single document. The keyword extraction unit extracts keywords from the key sentences.

Abstract: According to one embodiment, an apparatus for improving a language model of a speech recognition system includes an extracting unit, a classifying unit, and a setting unit. The extracting unit extracts user words from a user document provided by a user. The classifying unit classifies the user words based on a system lexicon of the speech recognition system. The setting unit sets weighting factor of a probability of the language model for at least one of the user words based on the classified result.

Abstract: According to one embodiment, an apparatus for improving a neural network language model of a speech recognition system includes a word classifying unit, a language model training unit and a vector incorporating unit. The word classifying unit classifies words in a lexicon of the speech recognition system. The language model training unit trains a class-based language model based on the classified result. The vector incorporating unit incorporates an output vector of the class-based language model into a position index vector of the neural network language model and use the incorporated vector as an input vector of the neural network language model.

Abstract: A data storage device and a flash memory control method with high efficiency are disclosed. The random access memory of the data storage device is allocated to provide a collection and update area for logical-to-physical address mapping tables that correspond to logical addresses recorded into the physical-to-logical address mapping table. When recording a logical address corresponding to a new logical-to-physical address mapping table that has not appeared in the collection and update area into the physical-to-logical address mapping table, the microcontroller of the data storage device is configured to collect the new logical-to-physical address mapping table into the collection and update area and perform an update of the new logical-to-physical address mapping table within the collection and update area.

Abstract: A data access method and device for parallel FFT computation. In the method, FFT data and twiddle factors are stored in multi-granularity parallel memories, and divided into groups throughout the computation flow according to a uniform butterfly representation. Each group of data involves multiple butterflies that support parallel computation. Meanwhile, according to the butterfly representation, it is convenient to generate data address and twiddle factor coefficient address for each group. With different R/W granularities, it is possible to read/write data and corresponding twiddle factors in parallel from the multi-granularity memories. The method and device further provide data access devices for parallel FFT computation. In the method and device, no conflict will occur during read/write operations of memories, and no extract step is required for sorting the read/written data. Further, the method and device can flexibly define the parallel granularity according to particular applications.

Abstract: A parallel bit reversal device and method. The device includes a parallel bit reversal unit, a butterfly computation and control unit, and a memory. The butterfly computation and control unit is coupled to the memory via a data bus. The parallel bit reversal unit is configured to bit-reverse butterfly group data used by the butterfly computation and control unit. The parallel bit reversal unit includes an address reversing logic coupled to the butterfly computation and control unit, and configured to perform mirror reversal and right-shift operations on a read address from the butterfly computation and control unit.

Abstract: A method and device for multi-granularity parallel FFT butterfly computation. The method and device read data and twiddle factors for computation in one butterfly group from the input buffers and the twiddle factor buffer at a time, perform multi-stage butterfly computation in parallel using uniform butterfly representations, and write the results back to the input buffers. The method and device greatly reduce the frequency for accessing the memory, improve speed for butterfly computation, and reduce power consumption. The method and device achieve multi-granularity butterfly computation of various data formats in a parallel and efficient manner. The method and device can specify the parallel granularity and data format for butterfly computation according to particular applications, and are applicable to FFT butterfly computation of balanced and unbalanced groups.

Abstract: A multi-granularity parallel FFT computation device including three memories, a butterfly computation device, a state control unit, a data reversing network and a first selector. The three memories are each a multi-granularity parallel memory, and store butterfly group data and twiddle factors corresponding to the butterfly group data. The butterfly computation device perform computations of a butterfly group based on the butterfly group data outputted from the first selector and the corresponding twiddle factors outputted from one of the memories, and write a computation result back to the other two memories. The device can read butterfly group data and corresponding twiddle factors in parallel from the multi-granularity parallel memories with a specific R/W granularity. No memory conflict will occur in the read operation, and no additional process is required for sorting the read/written data.

Abstract: A data storage device and a flash memory control method with a power recovery design. A microcontroller is configured to allocate a flash memory to provide a first block from the blocks to work as a run-time write block for reception of write data. During a power recovery process due to an unexpected power-off event that interrupted write operations on the first block, the microcontroller is configured to allocate the flash memory to provide a second block from the blocks for complete data recovery of the first block and to replace the first block as the run-time write block.

Abstract: A data storage device with flash memory and a flash memory control method are disclosed, in which the flash memory includes multi-level cells (MLCs) and single-level cells (SLCs). A microcontroller is configured to establish a first physical-to-logical address mapping table (F2H table) in a random access memory (RAM) for a first run-time write block containing MLCs. The microcontroller is further configured to establish a second F2H table in the RAM for a second run-time write block containing SLCs. When data that was previously stored in the first run-time write block with un-uploaded mapping information in the first F2H table is updated into the second run-time write block, the microcontroller is configured to update a logical-to-physical address mapping table (H2F table) in accordance with the first F2H table. The H2F table is provided within the flash memory.

Abstract: According to one aspect, there is provided an apparatus for improving a bilingual corpus including a plurality of sentence pairs of a first language and a second language and word alignment information of each of the sentence pairs, the apparatus comprises: an extracting unit for extracting a split candidate from word alignment information of a given sentence pair; a calculating unit for calculating split confidence of said split candidate; a comparing unit for comparing said split confidence and a pre-set threshold; and a splitting unit for splitting said given sentence pair at said split candidate in a case that said split confidence is larger than said pre-set threshold.

Abstract: A data storage device with flash memory and a flash memory control method are disclosed, which upload the physical-to-logical address mapping information of one block to the flash memory section by section. A microcontroller is configured to allocate a flash memory to provide a first run-time write block. Between a first write operation and a second write operation of the first run-time write block, the microcontroller updates a logical-to-physical address mapping table in accordance with just part of a first physical-to-logical address mapping table. The logical-to-physical address mapping table is provided within the flash memory. The first physical-to-logical address mapping table is established in the random access memory to record logical addresses corresponding to physical addresses of one block.

Abstract: A data storage device and a flash memory control method with high efficiency are disclosed. The random access memory of the data storage device is allocated to provide a collection and update area for logical-to-physical address mapping tables that correspond to logical addresses recorded into the physical-to-logical address mapping table. When recording a logical address corresponding to a new logical-to-physical address mapping table that has not appeared in the collection and update area into the physical-to-logical address mapping table, the microcontroller of the data storage device is configured to collect the new logical-to-physical address mapping table into the collection and update area and perform an update of the new logical-to-physical address mapping table within the collection and update area.

Abstract: A data storage device with flash memory and a flash memory control method are disclosed, in which the flash memory includes multi-level cells (MLCs) and single-level cells (SLCs). A microcontroller is configured to use the random access memory to cache data issued from the host before writing the data into the flash memory. The microcontroller is further configured to allocate the blocks of the flash memory to provide a first run-time write block containing multi-level cells and a second run-time write block containing single-level cells. Under control of the microcontroller, each physical page of data uploaded from the random access memory to the first run-time write block contains sequential data, and random data cached in the random access memory to form one physical page is written into the second run-time write block.

Abstract: A data storage device and a flash memory control method with high erasing efficiency are disclosed. A microcontroller is configured to maintain a plurality of logical-to-physical address mapping tables and a link table on a flash memory to record mapping information between a host and the flash memory. The link table indicates positions of the plurality of logical-to-physical address mapping tables, and each entry in the link table corresponds to one logical-to-physical address mapping table. When erasing user data of logical addresses corresponding to N logical-to-physical address mapping tables, the microcontroller is configured to invalidate N entries corresponding to the N logical-to-physical address mapping tables in the link table, where N is an integer.

Abstract: An apparatus for converting current to voltage includes a pair of current inputs, a differential voltage output connected to the pair of current inputs, a current summing node connected to the pair of current inputs through a first resistor branch, a common mode feedback node connected to the pair of current inputs through a second resistor branch, an amplifier operable to generate a current control signal based at least in part on a voltage at the common mode feedback node, and a current controller operable to control a current through the current summing node based at least in part on the current control signal.

Abstract: The present disclosure provides A data access method and device for parallel FFT computation. In the method, FFT data and twiddle factors are stored in multi-granularity parallel memories, and divided into groups throughout the computation flow according to a uniform butterfly representation. Each group of data involves multiple butterflies that support parallel computation. Meanwhile, according to the butterfly representation, it is convenient to generate data address and twiddle factor coefficient address for each group. With different R/W granularities, it is possible to read/write data and corresponding twiddle factors in parallel from the multi-granularity memories. The method and device further provide data access devices for parallel FFT computation. In the method and device, no conflict will occur during read/write operations of memories, and no extract step is required for sorting the read/written data.

Abstract: A method and device for multi-granularity parallel FFT butterfly computation. The method and device read data and twiddle factors for computation in one butterfly group from the input buffers and the twiddle factor buffer at a time, perform multi-stage butterfly computation in parallel using uniform butterfly representations, and write the results back to the input buffers. The method and device greatly reduce the frequency for accessing the memory, improve speed for butterfly computation, and reduce power consumption. The method and device achieve multi-granularity butterfly computation of various data formats in a parallel and efficient manner. The method and device can specify the parallel granularity and data format for butterfly computation according to particular applications, and are applicable to FFT butterfly computation of balanced and unbalanced groups.

Abstract: A multi-granularity parallel FFT computation device including three memories, a butterfly computation device, a state control unit, a data reversing network and a first selector. The three memories are each a multi-granularity parallel memory, and store butterfly group data and twiddle factors corresponding to the butterfly group data. The butterfly computation device perform computations of a butterfly group based on the butterfly group data outputted from the first selector and the corresponding twiddle factors outputted from one of the memories, and write a computation result back to the other two memories. The device can read butterfly group data and corresponding twiddle factors in parallel from the multi-granularity parallel memories with a specific R/W granularity. No memory conflict will occur in the read operation, and no additional process is required for sorting the read/written data.