ITR-NHS-DMC: Making Speech Recognition Pervasive by Migrating it Into Silicon

ITR-NHS-DMC：通过将语音识别迁移到芯片中来使其普及

• 批准号: 0426904
• 负责人: Rob Rutenbar
• 金额: --
• 依托单位: Carnegie-Mellon University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2004
• 资助国家: 美国
• 起止时间: 2004-09-01 至 2010-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0426904&HistoricalAwards=false
• 关键词: ITR; NHS; DMC; Making; Speech

NSF ITR Proposal 0426904Making Speech Recognition Pervasive by Migrating it Into SiliconRob A. Rutenbar (CMU), Tsuhan Chen (CMU), Robert W. Brodersen (U.C. Berkeley)ABSTRACTWhether running on a single cell phone or a conventional PC - all of today's state-of-the-art speech recognizers exist as complex software running on conventional computers. This is profoundly limiting for national and homeland security applications in which mobility or stealth are essential. Today's state-of-the-art speech recognizers fully occupy the resources of a modern desktop PC; but we cannot deploy such hardware in scenarios where size, covertness, long-life, and untethered operation are essential. Our cell phones last a week if we do not use them; they last a few hours when we actually speak to them. To remedy this, we must move the core of today's most successful speech recognition strategies directly into silicon. We propose to design a silicon speech recognition architecture that can offer at least 100 times better energy efficiency than today's software solutions. We will explore performance trade-offs by extending field programmable gate array (FPGA) emulation technology, so that proposed chip designs may be rapidly evaluated executing real-world problems involving hours of voice data. The Carnegie Mellon / Berkeley team brings decades of experience with silicon design, low-power design, and speech recognition to this effort. The goal of the project is to liberate speech recognition from the artificial constraints of its current software-only form, and to make it a reliable, pervasive technology for the field-oriented national and homeland security applications where it is today unsuitable.

摘要rob a . Rutenbar (CMU), Tsuhan Chen (CMU), Robert W. Brodersen（加州大学伯克利分校）摘要当今所有最先进的语音识别器，无论是在单个手机上还是在传统的PC上运行，都是以复杂的软件形式存在的，运行在传统的计算机上。这极大地限制了国家和国土安全方面的应用，而在这些应用中，机动性和隐身性是必不可少的。当今最先进的语音识别器完全占据了现代台式电脑的资源；但是，我们不能在尺寸、隐蔽性、长寿命和不受约束的操作必不可少的场景中部署这样的硬件。如果我们不使用手机，我们的手机可以维持一周；当我们和他们交谈时，他们会持续几个小时。为了解决这个问题，我们必须将当今最成功的语音识别策略的核心直接转移到芯片中。我们建议设计一种硅语音识别架构，它的能源效率至少是目前软件解决方案的100倍。我们将通过扩展现场可编程门阵列（FPGA）仿真技术来探索性能权衡，以便提出的芯片设计可以快速评估执行涉及数小时语音数据的实际问题。卡内基梅隆/伯克利团队在硅设计、低功耗设计和语音识别方面拥有数十年的经验。该项目的目标是将语音识别从目前的纯软件形式的人为限制中解放出来，并使其成为一种可靠的、普及的技术，适用于面向现场的国家和国土安全应用，而目前这种技术还不适合。