You never change things by fighting the existing reality. To change something, build a new model that makes the existing model obsolete.
The Importance of Detailed Requirements The purchase of an Automatic Speech Recognition (ASR) System is a challenging exercise. Consequently, if done poorly, the resulting program execution risks being a disaster. Spending time on writing requirements for speech recognition permits the evaluation and testing of ASR
The relationship between the cost and usability of speech recognition, often these are the factors that drive the reluctance to use speech recognition for simulation training. Furthermore, usability and expense are linked when deciding the acquisition of speech technologies. It costs a lot of money
Simulated air traffic control has been a desired feature for pilot training for many years. Becoming a copilot in a multi-crew passenger aircraft requires only 240 hours of flight time. Surprisingly to many, flight time does not always mean in an airplane, most of the
Vendor Accuracy is Meaningless! Why when accuracy would seem all-important? Let me clarify. Of course, speech recognition accuracy is an important metric. There are several measures of ASR Performance. Your ASR enabled application dictates which measure better determines usability. However, ASR accuracy figures quoted by
Are you buying a simulator with Automatic Speech Recognition (ASR)? Are you adding speech recognition to your existing simulation capabilities? The ASR buying decision is already complex. (see this Free Download). When choosing a speech recognition vendor, purchasers often overlook this key question. Should you
Using Artificial Grammar Limitations Speech recognition is a valuable addition to any simulation training system, but only if implemented correctly. There are many considerations for what implemented correctly means. In this article, we will discuss the use of artificial grammar limitations e.g., state-based grammar, and
Why this Post? When founding Verbyx in 2011, I found that although I understood the business and application of Automatic Speech Recognition (ASR) very well. Understanding speech recognition and the workings of an ASR required some work. I wanted to remedy that situation. Once again,
An acoustic model is used in automatic speech recognition to represent the relationship between an audio signal and the phonemes or other linguistic units that make up speech. A well trained acoustic model (often called a voice model) is critical in the performance of an
Introduction The previous post introduced the topic of unsupported phrases also called out-of-grammar (OOG). The Impact of Unsupported Phrases. The post explained that OOG is not specifically a speech recognition problem. However, serious thought and consideration of dealing with out-of-grammar inputs are vital. The consideration
In earlier posts, we discussed how we might specify and measure speech recognition accuracy when using a constrained grammar model. The definition of the required phrases was also explored. If we could trust the users of our system only to use the supported phrases, we