Speech recognition historically has been constrained to PC-based systems, telephone servers, and high-end cell phones and PDAs. But advances in recent years have brought low-cost speech-recognition processors into the realm of consumer electronics.
Today's speech-recognition processors contain more integration on chip, they're more accurate, and they're accompanied by better tools, making it relatively easy to add speech I/O to consumer products. Speech control of environmental lighting for the home represents one potential consumer application.
Types Of Speech Recognition Speech recognition (sometimes called voice recognition or VR) can be broadly divided into three classes: speaker-independent (SI), speaker-dependent (SD), and speaker verification (SV). Each has advantages that can be exploited in different applications. Products using SI require speech commands that work "out of the box" without user training.
For example, SI typically serves light controllers best. It's also better to use one SI command, called a "trigger," to get the light controller's attention โ just like we use names to trigger the attention of our associates. After triggering the product, it can listen for a set of multiple commands.
Products that incorporate speech recognition usually need a way to let the user know they have heard a command and are ready for further instruction. That is, they must let the user know where the product is in the control flow. The light controller will use a short tone since the flow is simple. This reduces the time spent interacting with the controller and is less intrusive if a false fire occurs .
Since speech is a natural interface for humans, speech recognition adds ease-of-use to products. Speech also extends beyond the user's physical reach. A speech-controlled light switch provides this kind of value. Perhaps the user is sitting down watching TV and the light is out of reach. Or, it may be too dark to see the light control. A simple voice command conveniently solves these dilemmas.
Design Considerations Because speech recognition is based on probabilistic functions, designers must strike a compromise between the importance of acceptance of commands that are included in a recognition set and rejection of commands that aren't included in the set. For instance, if the product must be very responsive and an occasional false acceptance (false firing) isn't catastrophic, the application developer may want to favor acceptance. Other applications can't tolerate false firing, such as a voice-operated oven control or a light controller.
Background noise is the bane of speech recognition. Both detection and recognition assume a reasonable signal-to-noise ratio (SNR) โ about 3:1 or better. Managing noise with directional or close-talking microphones is best when the application naturally allows for that approach.
Cost also is a factor. When an end user buys a product, the initial manufacturing cost has been marked up four to five times. Fortunately, the highly integrated speech processors that are now available contain the necessary microphone preamplifier, analog-to-digital converter (ADC), digital filters, core processor, digital-to-analog converter (DAC), and math engines.
They also come bundled with text-to-speaker-independent (T2SI) recognition and synthesis technologies. The chips can double as the primary controller of the consumer product functions, too, and they're priced competitively for consumer electronics. This results in little or no incremental increase in cost to add speech.
Light Controller Theory of Design The very features that make a VR light controller appealing also contribute to the challenges of speech recognition in this application. Recognizing a command at a distance in a home environment means competing with background noises like speech, TV, music, clattering dishes, and banging doors. Such an application also must work well for adults and children of both sexes.
Speech recognition is only as good as the integrity of the signal being processed, so proper design of the microphone circuit is fundamental. This circuit should be designed so that the combination of microphone, bias resistor, and preamplification stage make the best use of the ADC bits โ maximizing the use of bits for best resolution but not saturating. The design should account for the range of power that is likely for people who speak softly and loudly, and for the distances at which the light controller is likely to be used (typically up to about 10 ft.).
It's best to bias a light controller toward avoiding false fires. (Users occasionally may have to repeat the command in noisy situations.) This can be accomplished with the Quick T2SI tool settings. Keeping the command set's size as small as possible is important to minimize substitutions of the wrong commands. This is particularly true in noisy environments, such as the home. To maximize differentiation, the T2SI commands should differ as much as possible in sound and length.
Finally, the logic flow for the light controller must be simple and natural to use. The steps to navigate from getting the light controller's attention to reaching the active command set should be minimized to avoid user confusion. The trigger word should always be duplicated in the active command set so that the users can always reestablish their place in the flow. The trigger word should be easy to associate with the light controller function, and the active commands should be typical for light control. The flow chart illustrates the flow we will use (Fig. 1).
Hardware Design The Sensory VR Stamp is used in this example to simplify the development of the light controller. The VR Stamp is a low-cost module containing a Sensory RSC-4128 microprocessor, audio-circuit discrete capacitors and microphone preamplifier, 3.58-MHz crystal, reset circuit, and 128 kbytes of flash memory for program code.
It also has 128 kbits of serial EEPROM memory, which isn't used in the light-controller application (Fig. 2). The VR Stamp Toolkit comes with VR Stamps, Integrated Development Environment (IDE), Quick T2SI, FluentChip Library (a variety of speech recognition and synthesis functions, including T2SI), VR Stamp Programmer board, and supporting documentation.
In the voice-activated light-controller circuit, the VR Stamp module listens for spoken commands from the user. It then supplies a control signal to turn the light on and off and sets the desired lamp brightness by setting the duty cycle (Fig. 3).
A 120-V, 60-Hz ac line source powers the circuit. A transformer (T1) and a diode bridge (D1) convert and rectify ac to dc. The RSC-4128 operates from 2.4 to 3.6 V. A regulator (U1) then produces a stable 3.3-V source to the VR Stamp. A 3300- Ω resistor (R1) reduces the ac line current down to a few microamps so the RSC-4128 can detect when the voltage crosses the zero-threshold point.
Internal diodes prevent chip damage from overdriving. A diac/triac pair (U2/Q2) controls the ac line at the output plug (P2). A 100- ยต F capacitor (C3) must be present to filter out low-frequency ripples on VDD . Unstable VDD will couple into the audio circuitry and reduce voice-recognition accuracy.
Can you please tell me which the software that you used when designing a voice light controller.I need it for my project because I need to design an electronic circuit which is voice activated to controll a bedside lamp for a disabled person,please help .
Nonkuselo -October 02, 2008
it nice feature but i whant to implement in TV or setup box for on/off and chnnel up and down. i whant to know the cost of ic.
ravi -September 30, 2008
i nead a software which work on vice recognation example :a 20 line paragraph is there which is recorded in my vioce for 3 to 4 time now i am reading the same paragraph for example please call me it is urgent. no i am reading like please call me is urgent i have done a mistake at line it at the moment i skip the word it now the system will say it is urgent then i will say it is urgent to complete the paragraph so please help me in this regard mir masood ali
masood -June 15, 2007
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