National Laboratory on Machine Perception. Peking University, Beijing, China. {hanrq, zhaopei, gaoqin, zhangzp, wuhao, [email protected]}. Abstract.

ing deals with the problem of how to represent a given input spectro-temporal ..... ICASSP, 2007. [7] B.A. Olshausen and D.J Field, “Emergence of simple-cell re-.

phones running the Android operating system like the Nexus One and others becoming ... decision-tree tied 3-state HMMs with currently up to 10k states total.

2Human Language Technology, Center of Excellence, ... coding information. In other words ... the l1 norm of the weights of the linear combination of ba-.

also presented for call center applications (Petrushin,. 1999; Lee and Narayanan, 2005). Emotional speech recognition can be employed by therapists as a diag ...

to the best sequence of words uttered for a given acoustic se- quence [13, 17]. ... large proprietary speech corpus, comparing a very good state- based baseline to our ..... cal speech recognition pipelines, a better solution would be to write a ...

system for automatic transcription of broadcast news. The .... vocabulary gave little improvements, but made new types .... asymmetries of the peaks of the pdf's.

IC_55.Dysarthric Speech Recognition Using Kullback-Leibler Divergence-based Hidden Markov Model.pdf. IC_55.Dysarthric Speech Recognition Using Kullback-Leibler Divergence-based Hidden Markov Model.pdf. Open. Extract. Open with. Sign In. Main menu.

Gaussian mixture models (SGMM) as well as standard Gaussian mixture models, together with all commonly used ... widely available databases such as those provided by the. Linguistic Data Consortium (LDC). Thorough ... tion of DiagGmm objects, indexed

suitable filter-and-sum beamforming [2, 3], i.e. a combi- nation of filtered versions of all the microphone signals. In ... microphonic version of the well known TI connected digit recognition task) and Section 9 draws our ... a Recognition Directivi

energy speech signal while the other one is trained to recognize the low energy speech signal. Suppose we are given a clean training dataset X, we first perform ...

(Actually the expected value is a little more than $5 if we do not shuffle the pack after each pick and you are strategic). • If the prize is doubled, you get two tries to ...

Instead of designing feature detectors to be good for discriminating between classes ... where vi,hj are the binary states of visible unit i and hidden unit j, ai,bj are ...

used to train HMM systems for conversational telephone speech transcription using ..... compare acoustic and language model scaling for several it- erations of ...

This thesis investigates the use of discriminative criteria for training HMM pa- rameters for speech ... tures of this implementation include the use of lattices to represent alternative transcriptions of the ..... information from two sources : a st

best approach. 3.1. ... basis. Rather than limit the update to very small step sizes to prevent this, we ..... context-dependent states with ±2 phones of context and 150000 ... periments; all systems are built from scratch on top of fMPE features.

As we process each speaker we store the speaker-specific count and mean statistics in memory and then at the end of the speaker's data we directly increment ...

tied covariances [1], in which a number of full-rank matrices ... cal optimization package as originally used [3]. We also re- ... If we change Pj by a small amount ∆j , the ..... context-dependent states with ±2 phones of context and 150000.

application in a real environment. Michel Vacher1, Anthony Fleury2, Jean-François Serignat1, Norbert Noury2, Hubert Glasson1. 1Laboratory LIG, UMR ...

Following SAT training, feature- and model-space discriminative training are car- ried out under the boosted maximum mutual information (BMMI) criterion.

ing the SR features on top of our best discriminatively trained system allows for a 0.7% ... method for large vocabulary speech recognition. 1. ... of training data (typically greater than 50 hours for large vo- ... that best represent the test sampl

and a class-based language model that uses both the SPINE-1 and. SPINE-2 training data ..... that a class-based language model is the best choice for addressing these problems .... ing techniques for language modeling,” Computer Speech.

Department of Electrical Computer and Software Engineering ..... FSM is created to implement the bus interface between the FPGA and the Wolfson. Note that ...