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.

NSF ITR提案0426904通过将其迁移到有机硅A. rutenbar（CMU），Tsuhan Chen（CMU），Robert W. Brodersen（U.C. Berkeley）中，将其迁移到硅树脂中，均在单手机或传统的PC上进行了计算机的常规计算机的运行。这是对流动性或隐身至关重要的国家和国土安全应用的极大限制。当今的最先进的语音识别者完全占据了现代台式PC的资源；但是，我们不能在大小，秘密，长寿和不受束缚的操作至关重要的情况下部署这种硬件。如果我们不使用手机，我们的手机持续了一周；当我们实际与他们交谈时，他们持续了几个小时。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移至硅。我们建议设计一种硅语音识别体系结构，该体系结构的能源效率至少比当今的软件解决方案提高了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，以便可以迅速评估所提出的芯片设计，以执行涉及数小时的语音数据的真实世界问题。卡内基·梅隆（Carnegie Mellon） /伯克利（Berkeley）团队为这项工作带来了数十年的硅设计，低功率设计和语音认可的经验。该项目的目的是将语音识别从其当前仅限软件形式的人为约束中解放出来，并使其成为以现场为导向的国家和国土安全应用程序的可靠，普遍的技术，如今它不适合使用。