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我正在尝试在 Watson 的 Speech-To-Text 中指定关键字Unity SDK，但我不确定如何执行此操作。

详细信息页面未显示示例（请参见此处：https ://www.ibm.com/watson/developercloud/doc/speech-to-text/output.shtml ），

和其他论坛帖子是为 Java 应用程序编写的（请参阅此处：如何为 IBM Watson Speech2text 服务指定语音关键字？）。

我已经尝试RecognizeRequest像这样在“识别”函数中创建的类中对这些值进行硬编码，但没有成功：

**编辑——这个函数永远不会被调用——**

public bool Recognize(AudioClip clip, OnRecognize callback)
    {
        if (clip == null)
            throw new ArgumentNullException("clip");
        if (callback == null)
            throw new ArgumentNullException("callback");

        RESTConnector connector = RESTConnector.GetConnector(SERVICE_ID, "/v1/recognize");
        if (connector == null)
            return false;

        RecognizeRequest req = new RecognizeRequest();
        req.Clip = clip;
        req.Callback = callback;

        req.Headers["Content-Type"] = "audio/wav";
        req.Send = WaveFile.CreateWAV(clip);
        if (req.Send.Length > MAX_RECOGNIZE_CLIP_SIZE)
        {
            Log.Error("SpeechToText", "AudioClip is too large for Recognize().");
            return false;
        }
        req.Parameters["model"] = m_RecognizeModel;
        req.Parameters["continuous"] = "false";
        req.Parameters["max_alternatives"] = m_MaxAlternatives.ToString();
        req.Parameters["timestamps"] = m_Timestamps ? "true" : "false";
        req.Parameters["word_confidence"] = m_WordConfidence ? "true" :false";

        //these "keywords" and "keywords_threshold" and "keywordsThreshold" parameters
        //are just my guess for how to set these values            
        req.Parameters["keywords"] = new string[] {"fun", "match", "test" };
        req.Parameters["keywordsThreshold"] = .2;
        req.Parameters["keywords_threshold"] = .2;
        //end my test insertions

        req.OnResponse = OnRecognizeResponse;

        return connector.Send(req);
    }

但返回的SpeechRecognitionEvent结果值不包含任何keywords_result. 这是我的目标。我试图像这样查看keywords_result 对象中每个关键字的置信度，但该keywords_result对象返回为null.

private void OnRecognize(SpeechRecognitionEvent result) {
    Debug.Log("Recognizing!");
    m_ResultOutput.SendData(new SpeechToTextData(result));

    if (result != null && result.results.Length > 0) {
        if (m_Transcript != null)
            m_Transcript.text = "";

        foreach (var res in result.results) {
            //the res.keywords_result comes back as null
            foreach (var keyword in res.keywords_result.keyword) {
                string text = keyword.normalized_text;
                float confidence = keyword.confidence;
                Debug.Log(text + ": " + confidence);                                            
            }
        }
    }
}

有没有人在 Unity 或 C# 中使用 Watson 的 Speech-To-Text SDK 成功实施了关键字置信度评估？欢迎所有想法和建议。

PS这是我的第一篇文章：）

4

1 回答 1

3

原来我需要在“SendStart”函数中指定关键字，如下所示：

private void SendStart() {
        if (m_ListenSocket == null)
            throw new WatsonException("SendStart() called with null connector.");

        Dictionary<string, object> start = new Dictionary<string, object>();
        start["action"] = "start";
        start["content-type"] = "audio/l16;rate=" + m_RecordingHZ.ToString() + ";channels=1;";
        start["continuous"] = EnableContinousRecognition;
        start["max_alternatives"] = m_MaxAlternatives;
        start["interim_results"] = EnableInterimResults;
        start["word_confidence"] = m_WordConfidence;
        start["timestamps"] = m_Timestamps;

        //specify keywords here
        start["keywords"] = keywordsToCheck.ToArray();
        start["keywords_threshold"] = 0.05;
        //end additions here 

        m_ListenSocket.Send(new WSConnector.TextMessage(Json.Serialize(start)));
        m_LastStartSent = DateTime.Now;
    }

并编写一些代码在“ParseRecognizeResponse”函数中正确解析keyword_results：

private SpeechRecognitionEvent ParseRecognizeResponse(IDictionary resp){

        if (resp == null)
            return null;


        List<SpeechRecognitionResult> results = new List<SpeechRecognitionResult>();
        IList iresults = resp["results"] as IList;
        if (iresults == null)
            return null;

        foreach (var r in iresults)
        {
            IDictionary iresult = r as IDictionary;
            if (iresults == null)
                continue;

            SpeechRecognitionResult result = new SpeechRecognitionResult();

            //added this section, starting here
            IDictionary iKeywords_result = iresult["keywords_result"] as IDictionary;
            result.keywords_result = new KeywordResults();
            List<KeywordResult> keywordResults = new List<KeywordResult>();
            foreach (string key in keywordsToCheck) {
                if (iKeywords_result[key] != null) {
                    IList keyword_Results = iKeywords_result[key] as IList;
                    if (keyword_Results == null) {
                        continue;
                    }
                    foreach (var res in keyword_Results) {
                        IDictionary kw_resultDic = res as IDictionary;
                        KeywordResult keyword_Result = new KeywordResult();
                        keyword_Result.confidence = (double)kw_resultDic["confidence"];
                        keyword_Result.end_time = (double)kw_resultDic["end_time"];
                        keyword_Result.start_time = (double)kw_resultDic["start_time"];
                        keyword_Result.normalized_text = (string)kw_resultDic["normalized_text"];
                        keywordResults.Add(keyword_Result);
                    }
                }
            }
            result.keywords_result.keyword = keywordResults.ToArray();                   
            //ends here

            result.final = (bool)iresult["final"];

            IList ialternatives = iresult["alternatives"] as IList;
            if (ialternatives == null)
                continue;

            List<SpeechRecognitionAlternative> alternatives = new List<SpeechRecognitionAlternative>();
            foreach (var a in ialternatives)
            {
                IDictionary ialternative = a as IDictionary;
                if (ialternative == null)
                    continue;

                SpeechRecognitionAlternative alternative = new SpeechRecognitionAlternative();
                alternative.transcript = (string)ialternative["transcript"];
                if (ialternative.Contains("confidence"))
                    alternative.confidence = (double)ialternative["confidence"];

                if (ialternative.Contains("timestamps"))
                {
                    IList itimestamps = ialternative["timestamps"] as IList;

                    TimeStamp[] timestamps = new TimeStamp[itimestamps.Count];
                    for (int i = 0; i < itimestamps.Count; ++i)
                    {
                        IList itimestamp = itimestamps[i] as IList;
                        if (itimestamp == null)
                            continue;

                        TimeStamp ts = new TimeStamp();
                        ts.Word = (string)itimestamp[0];
                        ts.Start = (double)itimestamp[1];
                        ts.End = (double)itimestamp[2];
                        timestamps[i] = ts;
                    }

                    alternative.Timestamps = timestamps;
                }
                if (ialternative.Contains("word_confidence"))
                {
                    IList iconfidence = ialternative["word_confidence"] as IList;

                    WordConfidence[] confidence = new WordConfidence[iconfidence.Count];
                    for (int i = 0; i < iconfidence.Count; ++i)
                    {
                        IList iwordconf = iconfidence[i] as IList;
                        if (iwordconf == null)
                            continue;

                        WordConfidence wc = new WordConfidence();
                        wc.Word = (string)iwordconf[0];
                        wc.Confidence = (double)iwordconf[1];
                        confidence[i] = wc;
                    }

                    alternative.WordConfidence = confidence;
                }

                alternatives.Add(alternative);
            }
            result.alternatives = alternatives.ToArray();
            results.Add(result);
        }

        return new SpeechRecognitionEvent(results.ToArray());                        
    }

因此，现在，当 OnRecognize 通过此 SpeechRecognitionEvent 时，我已将用于显示替代词及其置信度分数的代码更改为显示关键字结果及其置信度分数，如下所示：

private void OnRecognize(SpeechRecognitionEvent result) {
    //Debug.Log("Recognizing!");
    m_ResultOutput.SendData(new SpeechToTextData(result));

    if (result != null && result.results.Length > 0) {
        if (m_Transcript != null)
            m_Transcript.text = "";

        foreach (var res in result.results) {
            //start keyword recognition changes here
            if (res.keywords_result != null) {
                if (res.keywords_result.keyword != null) {
                    foreach (var keyword in res.keywords_result.keyword) {
                        m_Transcript.text += string.Format("{0} ({1}, {2:0.00})\n",
                            keyword.normalized_text, res.final ? "Final" : "Interim", keyword.confidence);
                    }
                }
            }
            //end here                
        }
    }
}

请注意，使用关键字结果置信度值比进行一些硬编码检查以查看替代 Watson 是否与您的关键字匹配，然后在此处使用置信度值更有价值。检查keyword_results.keyword[].confidence 值时，置信度值会高得多，因为它已经在检查这些词。这是完成此过程并解析 SpeechRecognitionEvent 结果值以正确包含keywords_result 值的动力。

对于一些背景，我正在为阅读障碍儿童创建一个节奏游戏来学习单词形成，所以想想吉他英雄遇到芝麻街。

于 2016-10-09T09:19:19.150 回答