Smart Speakers

The primary audio paths for a smart speaker are between the device and the IVA or a network server using the Internet with a Wi-Fi or wired connection. On the input side, a speech signal containing a spoken command is sensed with the device’s microphone array, digitized and then uploaded to the IVA for signal processing and command interpretation. On the output side, digital audio content is transmitted from a Web server to the device, where it is converted from digital to analog, then finally to an acoustic signal as it is played over the device’s loudspeaker system.

Testing the overall end-to-end performance of a smart speaker’s primary input and output audio paths can be quite challenging for the following reasons: 

• Input to and output from a smart speaker are both acoustic, and acoustic test is by its nature more complex than electronic (analog or digital) audio test. Acoustic tests require calibrated microphones, usually an anechoic test chamber, and a quality loudspeaker system to stimulate DUT microphones.
• Smart speakers are inherently open-loop devices. On the input side, a signal (typically speech) is captured, digitized and then transmitted to a server somewhere as a digital audio file. To assess the input path performance, the audio file must be retrieved from the server and analyzed in comparison to the signal that was generated in the first place. On the output side, audio content that originates as an audio file on a server is streamed to the device where it is converted to analog and played on the device’s loudspeaker system. To assess the output path performance, the device’s loudspeaker output must be measured with a measurement microphone and compared with the original signal from the server. The original signal is often in the form of an encoded audio signal (e.g., MP3 or AAC), which requires that it be decoded before analysis.
• The A/D and D/A converters in the device will invariably have different sample rates than the audio analyzer, requiring some form of compensation during analysis.

One of the key attributes of transfer function analysis is that it provides a means of measuring the frequency response of a device using any broadband signal, including speech and music. This makes it an ideal choice for analyzing devices used for speech communication (i.e., smart speakers, smartphones, headset microphones, etc.). Many of these devices incorporate DSP algorithms that require the use of speech signals, and some are designed to block sinusoidal signals altogether. Transfer function analysis greatly simplifies measuring the frequency response of such devices.

An interaction with a smart speaker begins with a specific “wake word” or phrase, followed by a command. In their normal operating mode, smart speakers are in a semi-dormant state, but are always “listening” for the wake word, which triggers them to acquire and process a spoken command. In terms of speech recognition, smart speakers themselves are only capable of recognizing the wake word (or phrase). The more computationally-intensive speech recognition and subsequent processing is done by the Intelligent Virtual Assistant on a connected server. Depending upon the evaluation being performed, the wake word may be an integral part of the test process.