Add explainer for contextual biasing

explainers/contextual-biasing.md

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+# Explainer: Contextual Biasing for the Web Speech API
+
+## Introduction
+
+The Web Speech API provides powerful speech recognition capabilities to web applications. However, general-purpose speech recognition models can sometimes struggle with domain-specific terminology, proper nouns, or other words that are unlikely to appear in general conversation. This can lead to a frustrating user experience where the user's intent is frequently misrecognized.
+
+To address this, we introduce **contextual biasing** to the Web Speech API. This feature allows developers to provide "hints" to the speech recognition engine in the form of a list of phrases and boost values. By biasing the recognizer towards these phrases, applications can significantly improve the accuracy for vocabulary that is important in their specific context.
+
+## Why Use Contextual Biasing?
+
+### 1. **Improved Accuracy**
+By providing a list of likely phrases, developers can dramatically increase the probability of those phrases being recognized correctly. This is especially useful for words that are acoustically similar to more common words.
+
+### 2. **Enhanced User Experience**
+When speech recognition "just works" for the user's context, it leads to a smoother, faster, and less frustrating interaction. Users don't have to repeat themselves or manually correct transcription errors.
+
+### 3. **Enabling Specialized Applications**
+Contextual biasing makes the Web Speech API a more viable option for specialized applications in fields like medicine, law, science, or gaming, where precise and often uncommon terminology is essential.
+
+## Example Use Cases
+
+### 1. Voice-controlled Video Game
+A video game might have characters with unique names like "Zoltan," "Xylia," or "Grog." Without contextual biasing, a command like "Attack Zoltan" might be misheard as "Attack Sultan." By providing a list of character and location names, the game can ensure commands are understood reliably.
+
+### 2. E-commerce Product Search
+An online store can bias the speech recognizer towards its product catalog. When a user says "Show me Fujifilm cameras," the recognizer is more likely to correctly identify "Fujifilm" instead of a more common but similar-sounding word.
+
+### 3. Medical Dictation
+A web-based application for doctors could be biased towards recognizing complex medical terms, drug names, and procedures. This allows for accurate and efficient voice-based note-taking.
+
+## New API Components
+
+Contextual biasing is implemented through a new `phrases` attribute on the `SpeechRecognition` interface, which uses two new supporting interfaces: `SpeechRecognitionPhrase` and `SpeechRecognitionPhraseList`.
+
+### 1. `SpeechRecognition.phrases` attribute
+This attribute is assigned a `SpeechRecognitionPhraseList` object to provide contextual hints for the recognition session.
+
+### 2. `SpeechRecognitionPhrase` interface
+Represents a single phrase and its associated boost value.
+
+- `constructor(DOMString phrase, optional float boost = 1.0)`: Creates a new phrase object.
+- `phrase`: The text string to be boosted.
+- `boost`: A float between 0.0 and 10.0. Higher values make the phrase more likely to be recognized.
+
+### 3. `SpeechRecognitionPhraseList` interface
+Represents a collection of `SpeechRecognitionPhrase` objects. It can be created with an array of phrases and managed dynamically with `addItem()` and `removeItem()` methods.
+
+### Example Usage
+
+```javascript
+// A list of phrases relevant to our application's context.
+const phrases = [
+  { phrase: 'Zoltan', boost: 3.0 },
+  { phrase: 'Grog', boost: 2.0 },
+];
+
+// Create SpeechRecognitionPhrase objects.
+const phrases = phrases.map(p => new SpeechRecognitionPhrase(p.phrase, p.boost));
+
+// Create a SpeechRecognitionPhraseList.
+const phraseList = new SpeechRecognitionPhraseList(phrases);
+
+const recognition = new SpeechRecognition();
+// Assign the phrase list to the recognition instance.
+recognition.phrases = phraseList;
+
+// Some user agents (e.g. Chrome) might only support on-device contextual biasing.
+recognition.processLocally = true;
+
+recognition.onresult = (event) => {
+  const transcript = event.results[0][0].transcript;
+  console.log(`Result: ${transcript}`);
+};
+
+recognition.onerror = (event) => {
+  if (event.error === 'phrases-not-supported') {
+    console.warn('Contextual biasing is not supported by this browser/service.');
+  }
+};
+
+// Start recognition when the user clicks a button.
+document.getElementById('speak-button').onclick = () => {
+  recognition.start();
+};
+```
+
+## Conclusion
+
+Contextual biasing is a powerful enhancement to the Web Speech API that gives developers finer control over the speech recognition process. By allowing applications to provide context-specific hints, this feature improves accuracy, creates a better user experience, and makes voice-enabled web applications more practical for a wider range of specialized use cases.