Voice Recognition Ready for Consumer Devices
This looks like the year that voice recognition finally reaches the mainstream. Motorola unveiled “Mya, the 24-hour talking Internet” at the Oscars. Tellme.com and other startups are deploying voice portals that accept speech commands and read web content over a standard telephone. The latest Jaguar allows drivers to adjust the climate and sound systems using their voice.
Most of these services run on remote servers or PCs where plenty of processing power is available. But the Jaguar example is telling: CPU performance has reached the point that even an inexpensive embedded processor can perform useful voice recognition. Over the next few years, voice will become a common interface in a variety of non-PC devices, many of which will be running Linux.
Until recently, voice recognition required each user to train the system to recognize his or her particular speech patterns. Like most other software, however, voice recognition improves given faster processors and more memory. Recent products reduce training time dramatically. Speaker-independent software eliminates training entirely. To achieve highly accurate speaker-independent recognition with moderate processing requirements, designers must limit the context and vocabulary of the application. For example, a car needs to recognize only a few dozen words, including “temperature”, “radio”, and the numbers needed to select a station.
Lernout & Hauspie (http://www.lhsl.com/), a leading supplier of voice software, supplies speech engines for applications as simple as these, as well as far more complex ones. According to Klaus Schleicher, a director of product management at L&H, the simplest speech engine provides speaker-independent recognition of up to 100 words, but requires less than 200K of memory. L&H offers a more-powerful speech engine that can recognize up to 1,000 words, again without training. This engine requires 2MB of memory and can run on a 200MHz processor. This hardware costs a bit more, but is still easily obtainable for $30 today, and that price will drop over time. The larger vocabulary is suitable for applications such as a TV set-top box that can be programmed by speaking the name of a show or a hand-held PDA that can manage calendars and address books via voice.
Composing arbitrary text, such as an e-mail message, requires a much larger vocabulary. For this purpose, L&H has a speech engine with a 20,000-word vocabulary—twice as large as the average adult's. This engine requires some training, but only about five minutes per user. Even this large vocabulary doesn't require a full-blown PC or server; the company has demonstrated it using a 200MHz StrongArm processor and 32MB of memory. This speech engine could be incorporated into a webpad, allowing users to compose e-mail and other documents without using a keyboard.
One problem is that these speech engines are still not 100% reliable. The smaller the vocabulary, the smaller the error rate—after all, there are fewer words to confuse. In addition, a “command and control” application has natural opportunities to seek clarification. For example, if the user says “Turn off the TV” in a noisy room, the system might respond “I didn't understand that; please try again” or “Do you want the TV off?” In these limited-domain applications, the software actually interprets the voice input to determine its meaning, in this case, to turn off the TV. One possible interpretation of the input phonemes might be “turnips are meaty”, but the software would quickly discard this possibility as irrelevant in the context of controlling the television. This intelligent interpretation is called natural language processing (NLP). The combination of good voice recognition and a well-programmed NLP back end can produce a reliable system.
A working example is MIT's Jupiter system, a conversation interface for weather information built by the university's Spoken Language Systems group. You can call it (1-888-573-8255, but it is often busy) and ask about the weather anywhere in the U.S. or around the world. It uses a 500MHz Pentium III PC running Linux, but it hasn't been optimized to reduce CPU overhead. Jupiter has a vocabulary of about 2,000 words and is very usable. Text dictation, however, has a much larger vocabulary and an unbounded content domain: an e-mail message could have any subject matter, even turnips. NLP for this application is much harder and generally limited to putting nouns and verbs in the right places. After dictating a few hundred words into even the best speech engine, a user is likely to have to go back and correct at least a dozen errors.
Thus, for applications where a keyboard is available and the user can type reasonably well, typing is likely to be the most efficient interface for the foreseeable future. But L&H's Schleicher says, “the human voice is the most natural user interface for communication and computing on a variety of devices.” For command and control applications in cars, information appliances, set-top boxes and even PCs, voice recognition is an excellent interface. The hardware just needs the right programming—and the sound of your voice.
Fast/Flexible Linux OS Recovery
On Demand Now
In this live one-hour webinar, learn how to enhance your existing backup strategies for complete disaster recovery preparedness using Storix System Backup Administrator (SBAdmin), a highly flexible full-system recovery solution for UNIX and Linux systems.
Join Linux Journal's Shawn Powers and David Huffman, President/CEO, Storix, Inc.
Free to Linux Journal readers.Register Now!
- Google's Abacus Project: It's All about Trust
- Download "Linux Management with Red Hat Satellite: Measuring Business Impact and ROI"
- Seeing Red and Getting Sleep
- Secure Desktops with Qubes: Introduction
- Fancy Tricks for Changing Numeric Base
- Back to Backups
- Working with Command Arguments
- Secure Desktops with Qubes: Installation
- Linux Mint 18
- CentOS 6.8 Released
Until recently, IBM’s Power Platform was looked upon as being the system that hosted IBM’s flavor of UNIX and proprietary operating system called IBM i. These servers often are found in medium-size businesses running ERP, CRM and financials for on-premise customers. By enabling the Power platform to run the Linux OS, IBM now has positioned Power to be the platform of choice for those already running Linux that are facing scalability issues, especially customers looking at analytics, big data or cloud computing.
￼Running Linux on IBM’s Power hardware offers some obvious benefits, including improved processing speed and memory bandwidth, inherent security, and simpler deployment and management. But if you look beyond the impressive architecture, you’ll also find an open ecosystem that has given rise to a strong, innovative community, as well as an inventory of system and network management applications that really help leverage the benefits offered by running Linux on Power.Get the Guide