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DirectX 中的語音輸入

注意

本文與舊版 WinRT 原生 API 相關。 針對新的原生應用程式專案,我們建議使用 OpenXR API

本文說明如何在 DirectX 應用程式中實作語音命令加上小片語和句子辨識,以進行Windows Mixed Reality。

注意

本文中的程式碼片段會使用 C++/CX,而不是 C++17 相容的 C++/WinRT,這用於 C++ 全像攝影專案範本中。 這些概念相當於 C++/WinRT 專案,但您需要翻譯程式碼。

使用 SpeechRecognizer 進行連續語音辨識

本節說明如何使用連續語音辨識在應用程式中啟用語音命令。 本逐步解說會使用 HolographicVoiceInput 範例中的程式碼。 執行範例時,請說出其中一個已註冊色彩命令的名稱,以變更旋轉 Cube 的色彩。

首先,建立新的 Windows::Media::SpeechRecognition::SpeechRecognizer 實例。

HolographicVoiceInputSampleMain::CreateSpeechConstraintsForCurrentState

m_speechRecognizer = ref new SpeechRecognizer();

建立要接聽的辨識器語音命令清單。 在這裡,我們會建構一組命令來變更全像投影的色彩。 為了方便起見,我們也會建立稍後將用於命令的資料。

m_speechCommandList = ref new Platform::Collections::Vector<String^>();
   m_speechCommandData.clear();
   m_speechCommandList->Append(StringReference(L"white"));
   m_speechCommandData.push_back(float4(1.f, 1.f, 1.f, 1.f));
   m_speechCommandList->Append(StringReference(L"grey"));
   m_speechCommandData.push_back(float4(0.5f, 0.5f, 0.5f, 1.f));
   m_speechCommandList->Append(StringReference(L"green"));
   m_speechCommandData.push_back(float4(0.f, 1.f, 0.f, 1.f));
   m_speechCommandList->Append(StringReference(L"black"));
   m_speechCommandData.push_back(float4(0.1f, 0.1f, 0.1f, 1.f));
   m_speechCommandList->Append(StringReference(L"red"));
   m_speechCommandData.push_back(float4(1.f, 0.f, 0.f, 1.f));
   m_speechCommandList->Append(StringReference(L"yellow"));
   m_speechCommandData.push_back(float4(1.f, 1.f, 0.f, 1.f));
   m_speechCommandList->Append(StringReference(L"aquamarine"));
   m_speechCommandData.push_back(float4(0.f, 1.f, 1.f, 1.f));
   m_speechCommandList->Append(StringReference(L"blue"));
   m_speechCommandData.push_back(float4(0.f, 0.f, 1.f, 1.f));
   m_speechCommandList->Append(StringReference(L"purple"));
   m_speechCommandData.push_back(float4(1.f, 0.f, 1.f, 1.f));

您可以使用可能不在字典中的注音文字來指定命令。

m_speechCommandList->Append(StringReference(L"SpeechRecognizer"));
   m_speechCommandData.push_back(float4(0.5f, 0.1f, 1.f, 1.f));

若要將命令清單載入語音辨識器的條件約束清單中,請使用 SpeechRecognitionListConstraint 物件。

SpeechRecognitionListConstraint^ spConstraint = ref new SpeechRecognitionListConstraint(m_speechCommandList);
   m_speechRecognizer->Constraints->Clear();
   m_speechRecognizer->Constraints->Append(spConstraint);
   create_task(m_speechRecognizer->CompileConstraintsAsync()).then([this](SpeechRecognitionCompilationResult^ compilationResult)
   {
       if (compilationResult->Status == SpeechRecognitionResultStatus::Success)
       {
           m_speechRecognizer->ContinuousRecognitionSession->StartAsync();
       }
       else
       {
           // Handle errors here.
       }
   });

訂閱語音辨識器的SpeechContinuousRecognitionSession上的ResultGenerated事件。 此事件會在辨識其中一個命令時通知您的應用程式。

m_speechRecognizer->ContinuousRecognitionSession->ResultGenerated +=
       ref new TypedEventHandler<SpeechContinuousRecognitionSession^, SpeechContinuousRecognitionResultGeneratedEventArgs^>(
           std::bind(&HolographicVoiceInputSampleMain::OnResultGenerated, this, _1, _2)
           );

您的 OnResultGenerated 事件處理常式會在 SpeechContinuousRecognitionResultGeneratedEventArgs 實例中接收事件資料。 如果信賴度大於您定義的臨界值,您的應用程式應該注意事件發生。 儲存事件資料,以便您可以在稍後的更新迴圈中使用它。

HolographicVoiceInputSampleMain.cpp

// Change the cube color, if we get a valid result.
   void HolographicVoiceInputSampleMain::OnResultGenerated(SpeechContinuousRecognitionSession ^sender, SpeechContinuousRecognitionResultGeneratedEventArgs ^args)
   {
       if (args->Result->RawConfidence > 0.5f)
       {
           m_lastCommand = args->Result->Text;
       }
   }

在我們的範例程式碼中,我們會根據使用者的命令變更旋轉全像投影 Cube 的色彩。

HolographicVoiceInputSampleMain::Update

// Check for new speech input since the last frame.
   if (m_lastCommand != nullptr)
   {
       auto command = m_lastCommand;
       m_lastCommand = nullptr;

       int i = 0;
       for each (auto& iter in m_speechCommandList)
       {
           if (iter == command)
           {
               m_spinningCubeRenderer->SetColor(m_speechCommandData[i]);
               break;
           }

           ++i;
       }
   }

使用「單次」辨識

您可以設定語音辨識器來接聽使用者說話的片語或句子。 在此情況下,我們會套用 SpeechRecognitionTopicConstraint ,告知語音辨識器預期的輸入類型。 以下是此案例的應用程式工作流程:

  1. 您的應用程式會建立 SpeechRecognizer、提供 UI 提示,並開始接聽語音命令。
  2. 使用者說出片語或句子。
  3. 使用者語音的辨識會發生,並將結果傳回給應用程式。 此時,您的應用程式應該提供 UI 提示,以指出已發生辨識。
  4. 視您想要回應的信賴等級和語音辨識結果的信賴等級而定,您的應用程式可以處理結果並適當地回應。

本節說明如何建立 SpeechRecognizer、編譯條件約束,以及接聽語音輸入。

下列程式碼會編譯主題條件約束,在此案例中已針對 Web 搜尋進行優化。

auto constraint = ref new SpeechRecognitionTopicConstraint(SpeechRecognitionScenario::WebSearch, L"webSearch");
   m_speechRecognizer->Constraints->Clear();
   m_speechRecognizer->Constraints->Append(constraint);
   return create_task(m_speechRecognizer->CompileConstraintsAsync())
       .then([this](task<SpeechRecognitionCompilationResult^> previousTask)
   {

如果編譯成功,我們可以繼續使用語音辨識。

try
       {
           SpeechRecognitionCompilationResult^ compilationResult = previousTask.get();

           // Check to make sure that the constraints were in a proper format and the recognizer was able to compile it.
           if (compilationResult->Status == SpeechRecognitionResultStatus::Success)
           {
               // If the compilation succeeded, we can start listening for the user's spoken phrase or sentence.
               create_task(m_speechRecognizer->RecognizeAsync()).then([this](task<SpeechRecognitionResult^>& previousTask)
               {

結果接著會傳回至應用程式。 如果我們在結果中有足夠的信心,我們可以處理命令。 此程式碼範例會以至少中等信賴度來處理結果。

try
                   {
                       auto result = previousTask.get();

                       if (result->Status != SpeechRecognitionResultStatus::Success)
                       {
                           PrintWstringToDebugConsole(
                               std::wstring(L"Speech recognition was not successful: ") +
                               result->Status.ToString()->Data() +
                               L"\n"
                               );
                       }

                       // In this example, we look for at least medium confidence in the speech result.
                       if ((result->Confidence == SpeechRecognitionConfidence::High) ||
                           (result->Confidence == SpeechRecognitionConfidence::Medium))
                       {
                           // If the user said a color name anywhere in their phrase, it will be recognized in the
                           // Update loop; then, the cube will change color.
                           m_lastCommand = result->Text;

                           PrintWstringToDebugConsole(
                               std::wstring(L"Speech phrase was: ") +
                               m_lastCommand->Data() +
                               L"\n"
                               );
                       }
                       else
                       {
                           PrintWstringToDebugConsole(
                               std::wstring(L"Recognition confidence not high enough: ") +
                               result->Confidence.ToString()->Data() +
                               L"\n"
                               );
                       }
                   }

每當您使用語音辨識時,watch表示使用者已在系統隱私權設定中關閉麥克風的例外狀況。 這可能會在初始化或辨識期間發生。

catch (Exception^ exception)
                   {
                       // Note that if you get an "Access is denied" exception, you might need to enable the microphone
                       // privacy setting on the device and/or add the microphone capability to your app manifest.

                       PrintWstringToDebugConsole(
                           std::wstring(L"Speech recognizer error: ") +
                           exception->ToString()->Data() +
                           L"\n"
                           );
                   }
               });

               return true;
           }
           else
           {
               OutputDebugStringW(L"Could not initialize predefined grammar speech engine!\n");

               // Handle errors here.
               return false;
           }
       }
       catch (Exception^ exception)
       {
           // Note that if you get an "Access is denied" exception, you might need to enable the microphone
           // privacy setting on the device and/or add the microphone capability to your app manifest.

           PrintWstringToDebugConsole(
               std::wstring(L"Exception while trying to initialize predefined grammar speech engine:") +
               exception->Message->Data() +
               L"\n"
               );

           // Handle exceptions here.
           return false;
       }
   });

注意

有數個預先定義的 SpeechRecognitionScenarios 可用來優化語音辨識。

  • 若要優化聽寫,請使用聽寫案例。

    // Compile the dictation topic constraint, which optimizes for speech dictation.
    auto dictationConstraint = ref new SpeechRecognitionTopicConstraint(SpeechRecognitionScenario::Dictation, "dictation");
    m_speechRecognizer->Constraints->Append(dictationConstraint);
    
  • 針對語音 Web 搜尋,請使用下列 Web 特定案例條件約束。

    // Add a web search topic constraint to the recognizer.
    auto webSearchConstraint = ref new SpeechRecognitionTopicConstraint(SpeechRecognitionScenario::WebSearch, "webSearch");
    speechRecognizer->Constraints->Append(webSearchConstraint);
    
  • 使用表單條件約束來填寫表單。 在此情況下,最好套用您自己的文法,以填滿表單。

    // Add a form constraint to the recognizer.
    auto formConstraint = ref new SpeechRecognitionTopicConstraint(SpeechRecognitionScenario::FormFilling, "formFilling");
    speechRecognizer->Constraints->Append(formConstraint );
    
  • 您可以使用 SRGS 格式提供自己的文法。

使用連續辨識

如需連續聽寫案例,請參閱Windows 10 UWP 語音程式碼範例

處理品質降低

環境條件有時會干擾語音辨識。 例如,會議室可能太雜訊,或者使用者可能會太大聲地說話。 可能的話,語音辨識 API 會提供造成品質降低之條件的相關資訊。 這項資訊會透過 WinRT 事件推送至您的應用程式。 下列範例示範如何訂閱此事件。

m_speechRecognizer->RecognitionQualityDegrading +=
       ref new TypedEventHandler<SpeechRecognizer^, SpeechRecognitionQualityDegradingEventArgs^>(
           std::bind(&HolographicVoiceInputSampleMain::OnSpeechQualityDegraded, this, _1, _2)
           );

在我們的程式碼範例中,我們會將條件資訊寫入偵錯主控台。 應用程式可能想要透過 UI、語音合成和其他方法向使用者提供意見反應。 或者,當語音因暫時降低品質而中斷時,可能需要以不同的方式運作。

void HolographicSpeechPromptSampleMain::OnSpeechQualityDegraded(SpeechRecognizer^ recognizer, SpeechRecognitionQualityDegradingEventArgs^ args)
   {
       switch (args->Problem)
       {
       case SpeechRecognitionAudioProblem::TooFast:
           OutputDebugStringW(L"The user spoke too quickly.\n");
           break;

       case SpeechRecognitionAudioProblem::TooSlow:
           OutputDebugStringW(L"The user spoke too slowly.\n");
           break;

       case SpeechRecognitionAudioProblem::TooQuiet:
           OutputDebugStringW(L"The user spoke too softly.\n");
           break;

       case SpeechRecognitionAudioProblem::TooLoud:
           OutputDebugStringW(L"The user spoke too loudly.\n");
           break;

       case SpeechRecognitionAudioProblem::TooNoisy:
           OutputDebugStringW(L"There is too much noise in the signal.\n");
           break;

       case SpeechRecognitionAudioProblem::NoSignal:
           OutputDebugStringW(L"There is no signal.\n");
           break;

       case SpeechRecognitionAudioProblem::None:
       default:
           OutputDebugStringW(L"An error was reported with no information.\n");
           break;
       }
   }

如果您未使用 ref 類別來建立 DirectX 應用程式,您必須先取消訂閱事件,才能釋出或重新建立語音辨識器。 HolographicSpeechPromptSample 有一個常式,可停止辨識和取消訂閱事件。

Concurrency::task<void> HolographicSpeechPromptSampleMain::StopCurrentRecognizerIfExists()
   {
       return create_task([this]()
       {
           if (m_speechRecognizer != nullptr)
           {
               return create_task(m_speechRecognizer->StopRecognitionAsync()).then([this]()
               {
                   m_speechRecognizer->RecognitionQualityDegrading -= m_speechRecognitionQualityDegradedToken;

                   if (m_speechRecognizer->ContinuousRecognitionSession != nullptr)
                   {
                       m_speechRecognizer->ContinuousRecognitionSession->ResultGenerated -= m_speechRecognizerResultEventToken;
                   }
               });
           }
           else
           {
               return create_task([this]() { m_speechRecognizer = nullptr; });
           }
       });
   }

使用語音合成來提供可聽見的提示

全像攝影語音範例會使用語音合成來為使用者提供可聽見的指示。 本節說明如何建立合成的語音範例,然後透過 HRTF 音訊 API 播放它。

建議您在要求片語輸入時提供自己的語音提示。 提示也可以協助指出在連續辨識案例中可以說出語音命令的時機。 下列範例示範如何使用語音合成器來執行這項操作。 您也可以使用預先錄製的語音剪輯、視覺 UI 或要說的內容的另一個指標,例如,在提示不是動態的情況下。

首先,建立 SpeechSynthesizer 物件。

auto speechSynthesizer = ref new Windows::Media::SpeechSynthesis::SpeechSynthesizer();

您也需要包含要合成之文字的字串。

// Phrase recognition works best when requesting a phrase or sentence.
   StringReference voicePrompt = L"At the prompt: Say a phrase, asking me to change the cube to a specific color.";

語音是透過合成TextToStreamAsync 以非同步方式合成。 在這裡,我們會開始非同步工作來合成語音。

create_task(speechSynthesizer->SynthesizeTextToStreamAsync(voicePrompt), task_continuation_context::use_current())
       .then([this, speechSynthesizer](task<Windows::Media::SpeechSynthesis::SpeechSynthesisStream^> synthesisStreamTask)
   {
       try
       {

語音合成會以位元組資料流程的形式傳送。 我們可以使用該位元組資料流程來初始化 XAudio2 語音。 針對全像攝影程式碼範例,我們會將其播放為 HRTF 音訊效果。

Windows::Media::SpeechSynthesis::SpeechSynthesisStream^ stream = synthesisStreamTask.get();

           auto hr = m_speechSynthesisSound.Initialize(stream, 0);
           if (SUCCEEDED(hr))
           {
               m_speechSynthesisSound.SetEnvironment(HrtfEnvironment::Small);
               m_speechSynthesisSound.Start();

               // Amount of time to pause after the audio prompt is complete, before listening
               // for speech input.
               static const float bufferTime = 0.15f;

               // Wait until the prompt is done before listening.
               m_secondsUntilSoundIsComplete = m_speechSynthesisSound.GetDuration() + bufferTime;
               m_waitingForSpeechPrompt = true;
           }
       }

如同語音辨識,語音合成會在發生錯誤時擲回例外狀況。

catch (Exception^ exception)
       {
           PrintWstringToDebugConsole(
               std::wstring(L"Exception while trying to synthesize speech: ") +
               exception->Message->Data() +
               L"\n"
               );

           // Handle exceptions here.
       }
   });

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