[PDF] Top 20 Decision tree-based acoustic models for speech recognition

... The parameter estimation process for the DTs consists of a growing stage, followed by an optional bottom-up pruning stage. A binary DT is grown by splitting a node into two child nodes as shown in Figure 2. The training ... See full document

... all acoustic models for all languages are listed in Table ...new models achieve better performance than CNN, CMNN, and RMNN ...network-based models achieve excellent performances ... See full document

... Whereas speech is the primary traditional data driven techniques such as k-means means of communication between people it is preferable clustering or knowledge driven techniques such as to be used to communicate ... See full document

... of speech/music classification was studied by many ...of acoustic features, such as short time energy, zero-crossing rate, cepstrum coe ffi cients, spectral rollo ff , spectrum centroid and “loudness,” ... See full document

... environment, based on phonetically rich sentences extracted from the Swedish text corpus also available from ...of speech data: i) a database for speech recognition and dictation, ii) a ... See full document

... asymmetric acoustic modelling using selective decision tree merging between a bilingual model and an accented embedded speech model for Hindi and English multilingual speech ... See full document

... 535 speech utterances, and all of these utterances are used in the ...all based on a tenfold cross-validation ...final recognition result is the average of these ...emotion recognition model ... See full document

... The performance of this technique is very dependent on the selection of the threshold. If it is too small, phones might get adapted on a too small amount of data, which could lead to overfitting to the data. On the other ... See full document

... all models corresponding to different temporal ...the acoustic signal represented by the feature ...recorded speech signal as MFCCs. Decoding was then performed with an acoustic model, a ... See full document

... the speech recognition ...actual decision about recognition of a speech utterance by combining and optimizing the information conveyed by the acoustic and language ... See full document

... unnatural speech material ...automatic speech recognition technology to automate the intelligibility ...automatic speech alignment based on acoustic models that were ... See full document

... of speech are expressed concurrently in a unified framework of context-dependent multi-space probability distribution hidden semi-Markov model (HSMM) ...of decision trees [31]. These decision ... See full document

... HMM-based speech recognizer was selected as the frame-based baseline ...phoneme recognition accuracy, based on speech utterances in the development set, were used for the ... See full document

... dialog models. On the one hand we are using a classic dialog model based on a finite-state machine approach for the task-oriented part of the ...as speech recognition accuracy, fa- cial ... See full document

... representatives of these classes can often be deduced from a Bayesian network that extends the conventional hidden Markov models used in speech recognition. These extensions, in turn, can in many ... See full document

... the acoustic space into streams where the distributions may be e ffi cently clustered and ...state-dependent models being obtained by Maximum LikeLihood Estimation (MLE) based selection and weighting ... See full document

... The problem of temporary distortions It was that speech comparison samples of the same class can be used only if the timescale conversions of one of them. In other words, say the same sound with different ... See full document

... particularly speech. Parsed speech stands to benefit from practically every application envisioned for parsed text, including machine translation, infor- mation extraction, and language ...however, ... See full document

... Language models are used to constrain search in a decoder by limiting the number of possible words that need to be considered at any one point in the search which leads to faster execution and higher ...language ... See full document

... A Tree Trellis Based Fast Search for Finding the N Best Sentence Hypotheses in Continuous Speech Recognition A Tree Trellis Based Fast Search for Finding the N Best Sentence Hypotheses in Continuous S[.] ... See full document