feat:regex corrections

README.md

@@ -1,27 +1,106 @@
 # Utterance Corrections plugin
 
-- "secret speech", map some random utterance to something else so you can furtively give orders to your assistant
-- shortcuts, map shorter utterances or slang to utterances you know trigger the correct intent
-- manually correct bad STT transcriptions you experimentally determined to be common for you
+This plugin provides tools to correct or adjust speech-to-text (STT) outputs for better intent matching or improved user experience.
 
-This plugin checks a user defined json for utterance fixes `~/.local/share/mycroft/corrections.json`
+### Key Features:
+1. **"Secret Speech"**: Map random utterances to something else so you can furtively give orders to your assistant.
+2. **Shortcuts**: Map shorter utterances or slang to known utterances that trigger the correct intent.
+3. **Manual STT Fixes**: Correct common STT transcription errors you experimentally determined.
 
-fuzzy matching is used to determine if a utterance matches the transcription
-if >=0.85% similarity then the replacement is returned instead of the original transcription
+---
+
+## 1. Full Utterance Corrections
+
+This plugin checks a user-defined JSON file for **utterance fixes** at `~/.local/share/mycroft/corrections.json`.
+
+**Fuzzy matching** is used to determine if an utterance matches a transcription. If similarity is greater than or equal to **85%**, the replacement is returned instead of the original transcription.
+
+### Example: `corrections.json`
 ```json
 {
     "I hate open source": "I love open source",
     "do the thing": "trigger protocol 404"
 }
 ```
 
-you can also define unconditional replacements at word level `~/.local/share/mycroft/word_corrections.json`
+**Input**:  
+`"I hat open source"`  
+
+**Output**:  
+`"I love open source"`
+
+---
+
+## 2. Word-Level Corrections
+
+You can also define unconditional word-level replacements in `~/.local/share/mycroft/word_corrections.json`.  
+
+This is particularly useful when STT models repeatedly transcribe specific names or words incorrectly.
 
-for example whisper STT often gets artist names wrong, this allows you to correct them
+### Example: `word_corrections.json`
 ```json
 {
     "Jimmy Hendricks": "Jimi Hendrix",
     "Eric Klapptern": "Eric Clapton",
     "Eric Klappton": "Eric Clapton"
 }
-```
+```
+
+**Input**:  
+`"I love Jimmy Hendricks"`  
+
+**Output**:  
+`"I love Jimi Hendrix"`
+
+
+> **use case**: whisper STT often does this mistake in it's transcriptions
+
+---
+
+## 3. Regex-Based Corrections
+
+For more complex corrections, you can use **regular expressions** in `~/.local/share/mycroft/regex_corrections.json`.  
+
+This is useful for fixing consistent patterns in STT errors, such as replacing incorrect trigraphs.
+
+### Example: `regex_corrections.json`
+```json
+{
+    "\\bsh(\\w*)": "sch\\1"
+}
+```
+
+### Explanation:
+- **`\\bsh(\\w*)`**: Matches words starting with `sh` at a word boundary.
+- **`sch\\1`**: Replaces `sh` with `sch` and appends the rest of the word.
+
+### Example Usage:
+**Input**:  
+`"shalter is a switch"`  
+
+**Output**:  
+`"schalter is a switch"`
+
+> **use case**: citrinet german model often does this mistake in it's transcriptions
+
+---
+
+## Configuration Paths
+
+| File                      | Purpose                               |
+|---------------------------|---------------------------------------|
+| `corrections.json`        | Full utterance replacements.          |
+| `word_corrections.json`   | Word-level replacements.              |
+| `regex_corrections.json`  | Regex-based pattern replacements.     |
+
+All correction files are stored under:  
+`~/.local/share/mycroft/`
+
+---
+
+### Usage Scenarios
+- **Improve Intent Matching**: Ensure consistent STT output for accurate intent triggers.
+- **Fix Model-Specific Errors**: Handle recurring transcription mistakes in certain STT engines.
+- **Shortcut Commands**: Simplify complex commands with shorter phrases or slang.
+
+Let us know how you're using this plugin, and feel free to contribute regex examples to this README or new use cases! 🚀

ovos_utterance_corrections_transformer/__init__.py

@@ -3,7 +3,7 @@
 from json_database import JsonStorage
 from ovos_config.meta import get_xdg_base
 from ovos_plugin_manager.templates.transformers import UtteranceTransformer
-from ovos_utils.parse import match_one
+from ovos_utils.parse import match_one, MatchStrategy
 from ovos_utils.xdg_utils import xdg_data_home
 
 
@@ -13,17 +13,31 @@ def __init__(self, name="ovos-utterance-corrections", priority=1):
         super().__init__(name, priority)
         self.db = JsonStorage(path=f"{xdg_data_home()}/{get_xdg_base()}/corrections.json")
         self.words_db = JsonStorage(path=f"{xdg_data_home()}/{get_xdg_base()}/word_corrections.json")
+        self.regex_db = JsonStorage(path=f"{xdg_data_home()}/{get_xdg_base()}/regex_corrections.json")
+        self.confidence_threshold = 0.85  # Default threshold, configurable
+        self.match_strategy = MatchStrategy.DAMERAU_LEVENSHTEIN_SIMILARITY
 
     def transform(self, utterances: List[str], context: Optional[dict] = None) -> (list, dict):
         context = context or {}
 
-        # replace full utterance
+        # Step 1: Replace full utterance
         if utterances and self.db:
-            replacement, conf = match_one(utterances[0], self.db)  # TODO - match strategy from conf
-            if conf >= 0.85:  # TODO make configurable
+            replacement, conf = match_one(
+                utterances[0], self.db, strategy=self.match_strategy
+            )
+            if conf >= self.confidence_threshold:
                 return [replacement], context
 
-        # replace individual words
+        # Step 2: Apply regex replacements
+        if utterances and self.regex_db:
+            for idx in range(len(utterances)):
+                for pattern, replacement in self.regex_db.items():
+                    try:
+                        utterances[idx] = re.sub(pattern, replacement, utterances[idx])
+                    except re.error as e:
+                        print(f"Invalid regex pattern: {pattern} -> {e}")
+
+        # Step 3: Replace individual words
         if utterances and self.words_db:
             for idx in range(len(utterances)):
                 for w, r in self.words_db.items():