Learn from SMX West presenters about specific tactics SEOs can use to create content for voice and how to roll out voice search campaigns.
In a lively session at last week’s SMX West conference, three presenters made a strong case for the need to think creatively about optimising content for voice and virtual assistants. Overall, the message was that Google is actively devouring online content to serve up in response to voice queries, and yet there’s still quite a bit of competitive advantage to be gained in an atmosphere where SEOs may not yet have caught on to the range of opportunities for voice optimisation.
Sound, search and semantics: How form follows function
Upasna Gautam from Ziff Davis provided a detailed technical explanation of Google’s approach to Automatic Speech Recognition (ASR). She argued that only by learning about the form of Google’s voice processing technology will we be able to properly understand its function and deploy successful strategies.
Gautam explained that Google’s ASR is structured as a three-part process comprised of sound signal processing which converts speech into mathematical data; speech modeling which determines the meaning of the utterance; and delivery of relevant search results back to the voice assistant.
At every processing stage, Google uses quality metrics to gauge and improve accuracy. Some examples:
- Word error rate: measures recognition accuracy at the word level
- Semantic quality: measures how closely voice results match results of queries typed in by a user
- Perplexity: measures the quality of a language model by its ability to predict the next word in a sequence
- Out-of-vocabulary rate: measures how many words spoken by a user are not accounted for in the language model
- Latency: the time it takes to complete a voice search
Using these metrics and others, in combination with machine learning and neural networks, Google’s voice processing technology works to constantly improve results delivered to consumers. In light of this, SEO practitioners need to be able to design well structured and concise answers even to comparatively vague questions and need to understand the tradeoffs Google’s process is designed to make. Gautam suggested, for example, that Google will sometimes favor speed over accuracy, so that an answer to a query that scores lower on semantic quality may still outrank a higher scoring result if it can be delivered more quickly. – Read more