Implement real-time text appending to input field

1. Add _baseText variable to track text before recording starts
   - Preserves existing text when starting new recording session
   - Provides foundation for real-time appending

2. Update real-time result processing logic
   - Real-time results now immediately update the text field
   - Combine base text + current recognition text
   - Move cursor to end for better UX
   - Add intelligent spacing between segments

3. Improve final result handling
   - Final results update base text for next recording
   - Clean state management between recording sessions

4. Update recording status change logic
   - Capture base text when recording starts
   - Maintain proper state transitions

Now users can see their speech being converted to text in real-time directly in the input field, providing immediate visual feedback during speech recognition.

example/lib/main.dart

@@ -41,6 +41,9 @@ class _SpeechRecognitionPageState extends State<SpeechRecognitionPage> {
   String _currentText = '';
   String _errorMessage = '';
   List<String> _recognitionHistory = [];
+  
+  /// 本次录音开始前的文本内容（用于实时追加）
+  String _baseText = '';
 
   // 录音相关
   final List<String> _realtimeResults = []; // 存储实时识别片段
@@ -155,6 +158,7 @@ class _SpeechRecognitionPageState extends State<SpeechRecognitionPage> {
       _recognitionHistory.clear();
       _realtimeResults.clear();
       _currentText = '';
+      _baseText = ''; // 也清空基础文本
       _textController.clear();
       _errorMessage = '';
     });
@@ -472,19 +476,27 @@ class _SpeechRecognitionPageState extends State<SpeechRecognitionPage> {
         setState(() {
           if (result.recognizedWords.isNotEmpty) {
             if (result.finalResult) {
-              // 最终结果：追加到文本框
+              // 最终结果：确认当前文本，更新base text为下次录音做准备
-              print('📱 [Example] 最终识别结果，追加到文本框: ${result.recognizedWords}');
+              print('📱 [Example] 最终识别结果，确认文本: ${result.recognizedWords}');
-              String currentTextInBox = _textController.text;
+              _baseText = _textController.text; // 保存当前文本作为下次的基础
-              if (currentTextInBox.isNotEmpty &&
+              _currentText = ''; // 清空当前识别文本
-                  !currentTextInBox.endsWith(' ')) {
-                currentTextInBox += ' '; // 添加空格分隔
-              }
-              _textController.text = currentTextInBox + result.recognizedWords;
-              // 最终结果不需要更新_currentText，因为录音已结束
             } else {
-              // 实时结果：仅用于显示，不追加到文本框
+              // 实时结果：实时更新到输入框
-              print('📱 [Example] 实时识别: ${result.recognizedWords}');
+              print('📱 [Example] 实时识别，更新输入框: ${result.recognizedWords}');
               _currentText = result.recognizedWords;
+              
+              // 实时更新输入框内容 = 基础文本 + 当前识别文本
+              String newText = _baseText;
+              if (newText.isNotEmpty && !newText.endsWith(' ') && _currentText.isNotEmpty) {
+                newText += ' '; // 添加空格分隔
+              }
+              newText += _currentText;
+              
+              _textController.text = newText;
+              // 将光标移到最后
+              _textController.selection = TextSelection.fromPosition(
+                TextPosition(offset: newText.length),
+              );
             }
           }
         });
@@ -509,13 +521,13 @@ class _SpeechRecognitionPageState extends State<SpeechRecognitionPage> {
               if (_recognitionHistory.length > 10) {
                 _recognitionHistory.removeLast();
               }
-              // 清空当前文本，因为录音已结束
-              _currentText = '';
             });
           }
+          // 注意：不在这里清空_currentText，因为最终结果会处理
         } else {
-          // 开始录音时清空实时结果缓存
+          // 开始录音时记录当前文本作为基础，清空当前识别文本
           setState(() {
+            _baseText = _textController.text; // 记录录音开始前的文本
             _realtimeResults.clear();
             _currentText = ''; // 清空当前识别文本
           });