標題: Titlebook: Connectionist Speech Recognition; A Hybrid Approach Hervé A. Bourlard,Nelson Morgan Book 1994 Springer Science+Business Media New York 1994 [打印本頁] 作者: ACORN 時間: 2025-3-21 18:02
書目名稱Connectionist Speech Recognition影響因子(影響力)
作者: Obligatory 時間: 2025-3-21 22:22
Speech Recognition Using ANNst that will be required. Even if one assumes infinite computational power, an infinite storage and corresponding memory bandwidth, and an infinite amount of training data, it is still not certain that one could solve the ASR problem in a satisfactory way. It has also become clear that the use of hig作者: 膽大 時間: 2025-3-22 01:33 作者: 舔食 時間: 2025-3-22 07:33 作者: sinoatrial-node 時間: 2025-3-22 10:44
0893-3405 ed, though thereis no such unequivocal experimental result for these methods. ..Connectionist Speech Recognition. is of use to anyone intendingto use neural net978-1-4613-6409-2978-1-4615-3210-1Series ISSN 0893-3405 作者: V切開 時間: 2025-3-22 15:41
Analytical Theories and Stochastic Models,t that will be required. Even if one assumes infinite computational power, an infinite storage and corresponding memory bandwidth, and an infinite amount of training data, it is still not certain that one could solve the ASR problem in a satisfactory way. It has also become clear that the use of hig作者: V切開 時間: 2025-3-22 20:42
Examples of Contemporary CFD Simulations,uire nasty amounts of data for training. In short, the design of massively parallel systems is limited by the number of parameters that can be learned with available training data. It is likely that the only way truly massive systems can be built is with the help of prior information, e.g., connecti作者: PACK 時間: 2025-3-22 21:22 作者: muffler 時間: 2025-3-23 05:00 作者: 最高峰 時間: 2025-3-23 05:53 作者: COM 時間: 2025-3-23 10:31
Experimental Systemsvanced Technologies (Denver, CO), and more recently with Michael Cohen, Horacio Franco, and Victor Abrash of SRI (Stanford, CA). The results of this continuing work are presented here to show that the hybrid HMM/MLP approach can improve state-of-the-art large vocabulary, continuous speech recognition systems.作者: 失敗主義者 時間: 2025-3-23 17:14
Context-Dependent MLPs, current state-of-the-art continuous speech recognizers require HMMs with greater complexity, e.g., multiple densities per phone and/or context-dependent phone models. Will the consistent improvement we have seen in these tests be washed out in systems with more detailed models?作者: 尋找 時間: 2025-3-23 20:30
HMM/MLP and Predictive Modelsability that a particular acoustic vector is emitted at a given time only depends on the current state and the current acoustic vector. As a consequence, this model does not take account of the dynamic nature of the speech signal..作者: Focus-Words 時間: 2025-3-23 23:43 作者: 嫌惡 時間: 2025-3-24 03:58
Statistical Thermodynamics of Turbulence,ckson, 1990; Hertz, Krogh, & Palmer, 1991; Zu-rada, 1992]. For more information on learning algorithms, performance evaluation, and applications, see [Karayiannis & Venetsanopoulos, 1993]. For more references and application areas, see [Simpson, 1991].作者: insomnia 時間: 2025-3-24 08:30 作者: perimenopause 時間: 2025-3-24 12:11 作者: LATER 時間: 2025-3-24 16:16
0893-3405 ches into state of the art continuous speechrecognition systems based on hidden Markov models (HMMs) to improvetheir performance. In this framework, neural networks (and inparticular, multilayer perceptrons or MLPs) have been restricted towell-defined subtasks of the whole system, i.e. HMM emissionp作者: hurricane 時間: 2025-3-24 20:39 作者: auxiliary 時間: 2025-3-24 23:34 作者: Somber 時間: 2025-3-25 03:24
Coherent Structures in Turbulence,ability that a particular acoustic vector is emitted at a given time only depends on the current state and the current acoustic vector. As a consequence, this model does not take account of the dynamic nature of the speech signal..作者: 誘惑 時間: 2025-3-25 10:19
Hidden Markov Modelsical method of estimating the probabilistic functions of Markov chains.’ Shortly afterwards, they were extended to automatic speech recognition independently at CMU [Baker, 1975b] and IBM [Bakis, 1976; Jelinek, 1976].作者: PLIC 時間: 2025-3-25 11:53 作者: FLIRT 時間: 2025-3-25 18:52
System Tradeoffse also has consequences for training. A particular design choice implies some tradeoff between these requirements. Additionally, trained systems such as those considered here may require entirely different resources for training and recognition modes, and these will be traded off in different techniques.作者: 收養(yǎng) 時間: 2025-3-25 22:38
Statistical Pattern Classificationcontext of a long history of pattern recognition technology. Though specific methods are changing, the pattern recognition perspective continues to be useful for the description of many problems and their proposed solutions.作者: SUE 時間: 2025-3-26 01:35
Hidden Markov Modelsn modeling the lexicon words or the constituent speech units by Hidden Markov Models (HMMs) [Baker 1975a,; Jelinek 1976; Bahl et al.,1983; Levinson et al., 1983; Rabiner & Juang, 1986]. First described in [Baum & Petrie, 1966; Baum & Eagon, 1967; Baum, 1972], this formalism was proposed as a statist作者: 事與愿違 時間: 2025-3-26 06:56 作者: HAIL 時間: 2025-3-26 09:36 作者: 領(lǐng)先 時間: 2025-3-26 15:06 作者: 偏狂癥 時間: 2025-3-26 19:08 作者: 公豬 時間: 2025-3-26 23:23
Experimental Systemsp at ICSI (in Berkeley, CA), (and more particularly Chuck Wooters, Phil Kohn, and Steve Renais, currently at Cambridge), Hynek Hermansky of US West Advanced Technologies (Denver, CO), and more recently with Michael Cohen, Horacio Franco, and Victor Abrash of SRI (Stanford, CA). The results of this c作者: Palpitation 時間: 2025-3-27 05:07 作者: overrule 時間: 2025-3-27 05:49
System Tradeoffswever, word accuracy is only one measure of a practical speech recognition technique. Any computational method requires resources in the form of storage and communication (memory) bandwidth, as well as the ability to do the required arithmetic. The number of parameters used for a particular techniqu作者: POINT 時間: 2025-3-27 10:16
Training Hardware and Softwaren process. In particular, a speech recognizer using MLP-based approaches scales well with more phonetic categories for requirements of storage, memory bandwidth, and numerical computation. This is particularly true when one takes into account the parameter-sharing that occurs in the hidden layer(s) 作者: 值得尊敬 時間: 2025-3-27 17:25 作者: FEIGN 時間: 2025-3-27 17:59
HMM/MLP and Predictive Modelsmputationally tractable. One of these assumptions is the observation independence of the acoustic vectors. Indeed, it is usually assumed that the probability that a particular acoustic vector is emitted at a given time only depends on the current state and the current acoustic vector. As a consequen作者: Anhydrous 時間: 2025-3-28 00:11
Feature Extraction by MLPrn classification plays a crucial role, it is only part of the vast speech recognition task. In spite of the spectacular progress made over the last decade, unrestricted speech recognition is still out of reach, and it is suspected that part of the difficulty lies in the use of inappropriate feature作者: 背信 時間: 2025-3-28 04:54 作者: commonsense 時間: 2025-3-28 08:51
https://doi.org/10.1007/978-1-4020-6435-7For thirty years, . (ANNs) have been used for difficult problems in pattern recognition [Viglione, 1970]. Some of these problems, such as the pattern analysis of brain waves, have been characterized by a low signal-to-noise ratio; in some cases it was not even known what was signal and what was noise.作者: 沖突 時間: 2025-3-28 12:52
IntroductionFor thirty years, . (ANNs) have been used for difficult problems in pattern recognition [Viglione, 1970]. Some of these problems, such as the pattern analysis of brain waves, have been characterized by a low signal-to-noise ratio; in some cases it was not even known what was signal and what was noise.作者: Latency 時間: 2025-3-28 17:51 作者: 驚惶 時間: 2025-3-28 22:20
The Hybrid HMM/MLP Approachf the speech signal. However, notwithstanding their efficiency, standard HMM-based recognizers suffer from several weaknesses, mainly due to the many hypotheses required to make their optimization possible (see Chapter 3):作者: 反抗者 時間: 2025-3-29 00:21 作者: ingenue 時間: 2025-3-29 06:34 作者: 外面 時間: 2025-3-29 09:56 作者: Thrombolysis 時間: 2025-3-29 15:20
Fluid Mechanics and Its Applicationsn modeling the lexicon words or the constituent speech units by Hidden Markov Models (HMMs) [Baker 1975a,; Jelinek 1976; Bahl et al.,1983; Levinson et al., 1983; Rabiner & Juang, 1986]. First described in [Baum & Petrie, 1966; Baum & Eagon, 1967; Baum, 1972], this formalism was proposed as a statist作者: Awning 時間: 2025-3-29 18:05 作者: defuse 時間: 2025-3-29 21:34
Analytical Theories and Stochastic Models, performance currently achieved by state of the art systems is not yet at the level of a mature technology. Over the years, many technological innovations have boosted the level of performance for more and more difficult tasks. Some of the most significant of these innovations include: (1) pattern m作者: 臨時抱佛腳 時間: 2025-3-30 02:07 作者: HILAR 時間: 2025-3-30 06:56
,Towards “Real World Turbulence”,f the speech signal. However, notwithstanding their efficiency, standard HMM-based recognizers suffer from several weaknesses, mainly due to the many hypotheses required to make their optimization possible (see Chapter 3):作者: 緩解 時間: 2025-3-30 10:48
Statistical Thermodynamics of Turbulence,p at ICSI (in Berkeley, CA), (and more particularly Chuck Wooters, Phil Kohn, and Steve Renais, currently at Cambridge), Hynek Hermansky of US West Advanced Technologies (Denver, CO), and more recently with Michael Cohen, Horacio Franco, and Victor Abrash of SRI (Stanford, CA). The results of this c作者: antidote 時間: 2025-3-30 13:11 作者: Valves 時間: 2025-3-30 17:09
,Towards “Real World Turbulence”,wever, word accuracy is only one measure of a practical speech recognition technique. Any computational method requires resources in the form of storage and communication (memory) bandwidth, as well as the ability to do the required arithmetic. The number of parameters used for a particular techniqu作者: 單純 時間: 2025-3-30 22:20 作者: CT-angiography 時間: 2025-3-31 01:08 作者: 尊敬 時間: 2025-3-31 06:48 作者: 復習 時間: 2025-3-31 12:42 作者: B-cell 時間: 2025-3-31 16:36 作者: 刪除 時間: 2025-3-31 17:32 作者: 鐵砧 時間: 2025-4-1 00:34
978-1-4613-6409-2Springer Science+Business Media New York 1994作者: Hippocampus 時間: 2025-4-1 02:56
Connectionist Speech Recognition978-1-4615-3210-1Series ISSN 0893-3405
