Large-Scale Discriminative Modelling for Data-Intensive Speech and Language Processing
数据密集型语音和语言处理的大规模判别建模
基本信息
- 批准号:261540-2013
- 负责人:
- 金额:$ 1.82万
- 依托单位:
- 依托单位国家:加拿大
- 项目类别:Discovery Grants Program - Individual
- 财政年份:2014
- 资助国家:加拿大
- 起止时间:2014-01-01 至 2015-12-31
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
As the wireless Internet and smartphones have become more and more prevalent in our daily life, many service providers have used the so-called cloud-computing framework to deliver various types of speech and language related services to customers. Under this background, it is very easy and fast for these providers to accumulate massive amount of real-world data in their central servers. Therefore, it has become a very interesting research topic regarding how to take advantage of the mass data available in this unprecedented big data era to further boost up performance to next level for many real world applications. In this research program, we will study this problem in the context of data-intensive speech and language applications, such as automatic speech recognition, text categorization and spoken language processing. We will first focus our research on investigating new discriminative models that are effective to model the most important and pertinent information available in the massive training data, which may be noisy and unlabelled. Meanwhile, we will also design efficient learning algorithms that are flexible enough to take full advantage of currently popular parallel computing facilities, such as multi-core CPUs, GPUs and map-reduce based distributed computing platform. More specifically, based on our previous research on margin-based discriminative learning, we will study three important sub-topics in this research program: i) how to extract discriminative and compact features for speech and language data; ii) how to build flexible discriminative models capable of dealing with a vast quantity of data in data-intensive speech and language applications; iii) how to parallelize learning algorithms to efficiently solve large-scale optimization in model estimation. We believe these issues are critical for us to fully benefit from massive real-world data in many data-intensive speech and language applications. This research program will help to advance large-scale learning and automatic knowledge discovery technologies for many Canadian and International industrial IT sections that are based on the more and more popular cloud-computing model.
随着无线互联网和智能手机在我们的日常生活中越来越普遍,许多服务提供商已经使用所谓的云计算框架来向客户提供各种类型的语音和语言相关服务。在这种背景下,这些提供商在其中央服务器上积累海量现实世界数据变得非常容易和快捷。因此,如何利用这个史无前例的大数据时代的海量数据,进一步提升许多现实世界应用的性能,成为一个非常有趣的研究课题。在这个研究项目中,我们将在数据密集型语音和语言应用的背景下研究这一问题,例如自动语音识别、文本分类和口语处理。我们将首先将研究重点放在研究新的判别模型上,这些模型可以有效地对海量训练数据中最重要和最相关的信息进行建模,这些数据可能是噪声和未标记的。同时,我们还将设计高效的学习算法,这些算法足够灵活,可以充分利用目前流行的并行计算设施,如多核CPU、GPU和基于MAP-REDUTE的分布式计算平台。更具体地说,在前人对基于边界的判别学习研究的基础上,我们将研究三个重要的子课题:i)如何提取语音和语言数据的区分特征和紧凑特征;ii)如何在数据密集型语音和语言应用中建立灵活的能够处理海量数据的判别模型;iii)如何将学习算法并行化以有效地解决模型估计中的大规模优化问题。我们认为,这些问题对于我们在许多数据密集型语音和语言应用程序中充分受益于海量真实世界数据至关重要。这项研究计划将有助于推动加拿大和国际许多工业IT部门基于越来越流行的云计算模型的大规模学习和自动知识发现技术。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
数据更新时间:{{ journalArticles.updateTime }}
{{
item.title }}
{{ item.translation_title }}
- DOI:
{{ item.doi }} - 发表时间:
{{ item.publish_year }} - 期刊:
- 影响因子:{{ item.factor }}
- 作者:
{{ item.authors }} - 通讯作者:
{{ item.author }}
数据更新时间:{{ journalArticles.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ monograph.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ sciAawards.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ conferencePapers.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ patent.updateTime }}
Jiang, Hui其他文献
Transmission of multidrug-resistant tuberculosis in Beijing, China: An epidemiological and genomic analysis.
- DOI:
10.3389/fpubh.2022.1019198 - 发表时间:
2022 - 期刊:
- 影响因子:5.2
- 作者:
Yin, Jinfeng;Zhang, Hongwei;Gao, Zhidong;Jiang, Hui;Qin, Liyi;Zhu, Chendi;Gao, Qian;He, Xiaoxin;Li, Weimin - 通讯作者:
Li, Weimin
Optimization of a multilayer Laue lens system for a hard x-ray nanoprobe
用于硬 X 射线纳米探针的多层劳厄透镜系统的优化
- DOI:
10.1088/2040-8978/16/1/015002 - 发表时间:
2013 - 期刊:
- 影响因子:0
- 作者:
Jiang, Hui;Wang, Hua;Mao, Chengwen;Li, Aiguo;He, Yan;Dong, Zhaohui;Zheng, Yi - 通讯作者:
Zheng, Yi
Liver serine palmitoyltransferase activity deficiency in early life impairs adherens junctions and promotes tumorigenesis.
- DOI:
10.1002/hep.28845 - 发表时间:
2016-12 - 期刊:
- 影响因子:13.5
- 作者:
Li, Zhiqiang;Kabir, Inamul;Jiang, Hui;Zhou, Hongwen;Libien, Jenny;Zeng, Jianying;Stanek, Albert;Ou, Peiqi;Li, Kailyn R.;Zhang, Shane;Bui, Hai H.;Kuo, Ming-Shang;Park, Tae-Sik;Kim, Benjamin;Worgall, Tilla S.;Huan, Chongmin;Jiang, Xian-Cheng - 通讯作者:
Jiang, Xian-Cheng
An acyltransferase domain of FK506 polyketide synthase recognizing both an acyl carrier protein and coenzymeA as acyl donors to transfer allylmalonyl and ethylmalonyl units
FK506 聚酮合酶的酰基转移酶结构域识别酰基载体蛋白和辅酶 A 作为酰基供体以转移烯丙基丙二酰基和乙基丙二酰基单位
- DOI:
10.1111/febs.13296 - 发表时间:
2015-07-01 - 期刊:
- 影响因子:5.4
- 作者:
Jiang, Hui;Wang, Yue-Yue;Li, Yong-Quan - 通讯作者:
Li, Yong-Quan
High level of intraoperative lactate might predict acute kidney injury in aortic arch surgery via minimally invasive approach in patients with type A dissection.
- DOI:
10.3389/fcvm.2023.1188393 - 发表时间:
2023 - 期刊:
- 影响因子:3.6
- 作者:
Lyu, Ying;Liu, Yu;Xiao, Xiong;Yang, Zhonglu;Ge, Yuguang;Jiang, Hui - 通讯作者:
Jiang, Hui
Jiang, Hui的其他文献
{{
item.title }}
{{ item.translation_title }}
- DOI:
{{ item.doi }} - 发表时间:
{{ item.publish_year }} - 期刊:
- 影响因子:{{ item.factor }}
- 作者:
{{ item.authors }} - 通讯作者:
{{ item.author }}
{{ truncateString('Jiang, Hui', 18)}}的其他基金
Exploring New Neural Computing Models for Natural Language Understanding
探索自然语言理解的新神经计算模型
- 批准号:
RGPIN-2018-05870 - 财政年份:2022
- 资助金额:
$ 1.82万 - 项目类别:
Discovery Grants Program - Individual
Exploring New Neural Computing Models for Natural Language Understanding
探索自然语言理解的新神经计算模型
- 批准号:
RGPIN-2018-05870 - 财政年份:2021
- 资助金额:
$ 1.82万 - 项目类别:
Discovery Grants Program - Individual
Exploring New Neural Computing Models for Natural Language Understanding
探索自然语言理解的新神经计算模型
- 批准号:
RGPIN-2018-05870 - 财政年份:2020
- 资助金额:
$ 1.82万 - 项目类别:
Discovery Grants Program - Individual
Exploring New Neural Computing Models for Natural Language Understanding
探索自然语言理解的新神经计算模型
- 批准号:
522577-2018 - 财政年份:2019
- 资助金额:
$ 1.82万 - 项目类别:
Discovery Grants Program - Accelerator Supplements
Exploring New Neural Computing Models for Natural Language Understanding
探索自然语言理解的新神经计算模型
- 批准号:
RGPIN-2018-05870 - 财政年份:2019
- 资助金额:
$ 1.82万 - 项目类别:
Discovery Grants Program - Individual
Exploring New Neural Computing Models for Natural Language Understanding
探索自然语言理解的新神经计算模型
- 批准号:
522577-2018 - 财政年份:2018
- 资助金额:
$ 1.82万 - 项目类别:
Discovery Grants Program - Accelerator Supplements
Exploring New Neural Computing Models for Natural Language Understanding
探索自然语言理解的新神经计算模型
- 批准号:
RGPIN-2018-05870 - 财政年份:2018
- 资助金额:
$ 1.82万 - 项目类别:
Discovery Grants Program - Individual
Large-Scale Discriminative Modelling for Data-Intensive Speech and Language Processing
数据密集型语音和语言处理的大规模判别建模
- 批准号:
261540-2013 - 财政年份:2017
- 资助金额:
$ 1.82万 - 项目类别:
Discovery Grants Program - Individual
Large-Scale Discriminative Modelling for Data-Intensive Speech and Language Processing
数据密集型语音和语言处理的大规模判别建模
- 批准号:
261540-2013 - 财政年份:2016
- 资助金额:
$ 1.82万 - 项目类别:
Discovery Grants Program - Individual
Large-Scale Discriminative Modelling for Data-Intensive Speech and Language Processing
数据密集型语音和语言处理的大规模判别建模
- 批准号:
261540-2013 - 财政年份:2015
- 资助金额:
$ 1.82万 - 项目类别:
Discovery Grants Program - Individual
相似国自然基金
基于热量传递的传统固态发酵过程缩小(Scale-down)机理及调控
- 批准号:22108101
- 批准年份:2021
- 资助金额:30 万元
- 项目类别:青年科学基金项目
基于Multi-Scale模型的轴流血泵瞬变流及空化机理研究
- 批准号:31600794
- 批准年份:2016
- 资助金额:22.0 万元
- 项目类别:青年科学基金项目
针对Scale-Free网络的紧凑路由研究
- 批准号:60673168
- 批准年份:2006
- 资助金额:25.0 万元
- 项目类别:面上项目
相似海外基金
Renewal application: How do ecological trade-offs drive ectomycorrhizal fungal community assembly? Fine- scale processes with large-scale implications
更新应用:生态权衡如何驱动外生菌根真菌群落组装?
- 批准号:
MR/Y011503/1 - 财政年份:2025
- 资助金额:
$ 1.82万 - 项目类别:
Fellowship
Traversing the Gray Zone with Scale-aware Turbulence Closures
通过尺度感知的湍流闭合穿越灰色区域
- 批准号:
2337399 - 财政年份:2024
- 资助金额:
$ 1.82万 - 项目类别:
Standard Grant
Collaborative Research: NCS-FR: Individual variability in auditory learning characterized using multi-scale and multi-modal physiology and neuromodulation
合作研究:NCS-FR:利用多尺度、多模式生理学和神经调节表征听觉学习的个体差异
- 批准号:
2409652 - 财政年份:2024
- 资助金额:
$ 1.82万 - 项目类别:
Standard Grant
Collaborative Research: RUI: Continental-Scale Study of Jura-Cretaceous Basins and Melanges along the Backbone of the North American Cordillera-A Test of Mesozoic Subduction Models
合作研究:RUI:北美科迪勒拉山脊沿线汝拉-白垩纪盆地和混杂岩的大陆尺度研究——中生代俯冲模型的检验
- 批准号:
2346565 - 财政年份:2024
- 资助金额:
$ 1.82万 - 项目类别:
Standard Grant
CRII: OAC: A Compressor-Assisted Collective Communication Framework for GPU-Based Large-Scale Deep Learning
CRII:OAC:基于 GPU 的大规模深度学习的压缩器辅助集体通信框架
- 批准号:
2348465 - 财政年份:2024
- 资助金额:
$ 1.82万 - 项目类别:
Standard Grant
Investigating Multi-Scale Dynamical Processes Amplifying Storm Surges
研究放大风暴潮的多尺度动力学过程
- 批准号:
2342516 - 财政年份:2024
- 资助金额:
$ 1.82万 - 项目类别:
Standard Grant
Collaborative Research: RUI: Continental-Scale Study of Jura-Cretaceous Basins and Melanges along the Backbone of the North American Cordillera-A Test of Mesozoic Subduction Models
合作研究:RUI:北美科迪勒拉山脊沿线汝拉-白垩纪盆地和混杂岩的大陆尺度研究——中生代俯冲模型的检验
- 批准号:
2346564 - 财政年份:2024
- 资助金额:
$ 1.82万 - 项目类别:
Standard Grant
Collaborative Research: OAC Core: Distributed Graph Learning Cyberinfrastructure for Large-scale Spatiotemporal Prediction
合作研究:OAC Core:用于大规模时空预测的分布式图学习网络基础设施
- 批准号:
2403312 - 财政年份:2024
- 资助金额:
$ 1.82万 - 项目类别:
Standard Grant
Continuous, Large-scale Manufacturing of Functionalized Silver Nanowire Transparent Conducting Films
功能化银纳米线透明导电薄膜的连续大规模制造
- 批准号:
2422696 - 财政年份:2024
- 资助金额:
$ 1.82万 - 项目类别:
Standard Grant
Collaborative Research: MRA: A functional model of soil organic matter composition at continental scale
合作研究:MRA:大陆尺度土壤有机质组成的功能模型
- 批准号:
2307253 - 财政年份:2024
- 资助金额:
$ 1.82万 - 项目类别:
Standard Grant