START OF PREVIOUS DISCUSSION
user:recognition = new webkitSpeechRecognition();
    recognition.continuous = true;
    recognition.interimResults = true;

    let fullTranscript = "\n";

    recognition.onresult = function (event) {
        var interimTranscript = '';

        for (var i = event.resultIndex; i < event.results.length; ++i) {
            if (event.results[i].isFinal) {
                fullTranscript += event.results[i][0].transcript;
            } else {
                interimTranscript += event.results[i][0].transcript;
            }
        }

        console.log('Full Transcript:', fullTranscript);

        let inp = document.querySelector('.overlay-section p');
        inp.textContent = fullTranscript + interimTranscript;
    };

    recognition.onend = () => {
        startRecognition();
    };

    function startRecognition() {
        recognition.start();
    }

make it so every it saves every fullTranscript/isFinal in a list the following:
"start":"TIME IT STARTED"
"tts":"FULL TRANSCRIPT"
"audio":"THE AUDIO CORRESPONDING TO THE EXACT FULL TRANSCRIPT SECTION"
"end":"TIME IT ENDED"
robot:To achieve this, you would need to modify the code to capture timestamps and additionally, you would need a way to record and match the audio to the corresponding transcript. Unfortunately, the Web Speech API doesn’t directly provide a means to capture audio blobs tied to interim results. One workaround could be to simultaneously record the entire audio session using the MediaRecorder API and then, post-processing, split the audio according to the timestamps you’ve captured for each transcript section.<br/><br/>Here is a basic outline of how you can modify the JavaScript code to capture the timestamps:<br/><pre><code class="javascript"><br/>const recognition = new webkitSpeechRecognition();<br/>recognition.continuous = true;<br/>recognition.interimResults = true;<br/><br/>let fullTranscript = “”;<br/>let transcriptList = [];<br/><br/>// Placeholder function to capture audio. You’ll need to replace this with actual audio capture logic<br/>function recordAudio() {<br/>  console.log(“Start audio recording here”);<br/>}<br/><br/>recognition.onresult = function (event) {<br/>    let interimTranscript = ‘’;<br/>    let startTime = null;<br/>    let endTime = null;<br/>    let isFinal = false;<br/><br/>    for (let i = event.resultIndex; i &lt; event.results.length; ++i) {<br/>        endTime = new Date().toISOString(); // Update the end time to the current timestamp<br/><br/>        if (event.results[i].isFinal) {<br/>            startTime = startTime || endTime; // Set the start time if not already set<br/>            fullTranscript += event.results[i][0].transcript;<br/>            isFinal = true;<br/>        } else {<br/>            interimTranscript += event.results[i][0].transcript;<br/>            startTime = startTime || new Date().toISOString(); // Set the start time on the first interim result<br/>        }<br/>    }<br/><br/>    console.log(‘Full Transcript:’, fullTranscript);<br/><br/>    let inp = document.querySelector(‘.overlay-section p’);<br/>    inp.textContent = fullTranscript + interimTranscript;<br/><br/>    // Only save to the list if we have a final transcript<br/>    if (isFinal) {<br/>        transcriptList.push({<br/>            “start”: startTime,<br/>            “tts”: fullTranscript,<br/>            “audio”: null, // Placeholder. Implement audio extraction logic<br/>            “end”: endTime<br/>        });<br/>        // Record and reset the start time for the next final result<br/>        startTime = null;<br/>    }<br/>};<br/><br/>recognition.onend = () =&gt; {<br/>    startRecognition();<br/>};<br/><br/>function startRecognition() {<br/>    recognition.start();<br/>    recordAudio(); // Call audio recording when starting recognition<br/>}<br/><br/>// Call <code>startRecognition</code> to kick things off<br/>startRecognition();<br/><br/>// Implementation of audio logic will be required here</code></pre><br/><br/>It’s important to note that this code does not yet record audio. To implement audio recording, you would use the MediaRecorder API, which involves requesting permission to use the user’s microphone, creating a new MediaRecorder instance, starting it at the same time as you start the speech recognition, and handling the <code>dataavailable</code> event to save the audio data parts into an array.<br/><br/>After you’ve recorded the full audio session, you can use the timestamps to try and split the audio. However, synchronizing the exact audio with each “final” recognition result can be quite challenging and might require audio analysis or some advanced buffer manipulation because the <code>webkitSpeechRecognition</code> API does not provide event-specific audio chunks.<br/><br/>This is a fairly complex problem and the provided solution only outlines the starting point for tracking timestamps with recognized speech, without solving the audio synchronization aspect. If audio syncing is a critical feature, consider using dedicated speech-to-text services that provide transcriptions alongside the corresponding audio.
END OF PREVIOUS DISCUSSION
user: ive already use the media player for something, so can u adapt this idea to my code? here it is:
let recognition;
let audioContext;
let analyser;
let microphone;

function awakePandoraEars() {
    recognition = new webkitSpeechRecognition();
    recognition.continuous = true;
    recognition.interimResults = true;

    let fullTranscript = "\n";

    recognition.onresult = function (event) {
        var interimTranscript = '';

        for (var i = event.resultIndex; i < event.results.length; ++i) {
            if (event.results[i].isFinal) {
                fullTranscript += event.results[i][0].transcript;
            } else {
                interimTranscript += event.results[i][0].transcript;
            }
        }

        console.log('Full Transcript:', fullTranscript);

        let inp = document.querySelector('.overlay-section p');
        inp.textContent = fullTranscript + interimTranscript;
    };

    recognition.onend = () => {
        startRecognition();
    };

    function startRecognition() {
        recognition.start();
    }

    startRecognition();

    audioContext = new (window.AudioContext || window.webkitAudioContext)();
    analyser = audioContext.createAnalyser();

    navigator.mediaDevices.getUserMedia({ audio: true })
        .then((stream) => {
            handleSuccess(stream);
            startRecognition(); // Start speech recognition after getting user media
        })
        .catch((error) => {
            console.error('Error accessing microphone:', error);
        });

    function handleSuccess(stream) {
        microphone = audioContext.createMediaStreamSource(stream);
        microphone.connect(analyser);

        analyser.fftSize = 256;
        const bufferLength = analyser.frequencyBinCount;
        const dataArray = new Uint8Array(bufferLength);

        function back(stream) {
            draw('visualizer');
            draw('mirroredVisualizer');
            draw('visualizerdown', down = true);
            draw('mirroredVisualizerdown', down = true);

            const visualizerCanvas = document.getElementById('visualizer');
            const mirroredCanvas = document.getElementById('mirroredVisualizer');
            const visualizerCanvasDown = document.getElementById('visualizerdown');
            const mirroredCanvasDown = document.getElementById('mirroredVisualizerdown');
            resizeCanvas();

            window.addEventListener('resize', resizeCanvas);

            function resizeCanvas() {
                const containerWidth = window.innerWidth / 2;
                const containerHeight = window.innerHeight;

                visualizerCanvas.width = containerWidth;
                visualizerCanvas.height = containerHeight;
                mirroredCanvas.width = containerWidth;
                mirroredCanvas.height = containerHeight;
                visualizerCanvasDown.width = containerWidth;
                visualizerCanvasDown.height = containerHeight;
                mirroredCanvasDown.width = containerWidth;
                mirroredCanvasDown.height = containerHeight;
            }

            function draw(canvasId, down = false) {
                const canvas = document.getElementById(canvasId);
                const ctx = canvas.getContext('2d');

                function drawFrame() {
                    analyser.getByteFrequencyData(dataArray);

                    ctx.clearRect(0, 0, canvas.width, canvas.height);

                    const barWidth = (canvas.width / bufferLength);

                    dataArray.forEach((value, index) => {
                        const barHeight = 2 * value;
                        let x;

                        x = index * barWidth;

                        ctx.fillStyle = `rgba(${barHeight / 2}, 0, ${-barHeight / 2 + 256}, 0.2)`;
                        if (down) {
                            ctx.fillRect(x, 0, barWidth, barHeight);
                        } else {
                            ctx.fillRect(x, canvas.height - barHeight, barWidth, barHeight);
                        }

                    });

                    requestAnimationFrame(drawFrame);
                }

                drawFrame();
            }

            window.onbeforeunload = function () {
                if (audioContext.state === 'running') {
                    audioContext.close();
                }
            };
        }

        back();
    }
}

function putToSleep() {
    clearCanvas('visualizer');
    clearCanvas('mirroredVisualizer');
    clearCanvas('visualizerdown');
    clearCanvas('mirroredVisualizerdown');

    if (audioContext && audioContext.state === 'running') {
        audioContext.close();
    }
    if (recognition && recognition.abort) {
        recognition.abort();
    }
    if (microphone) {
        microphone.disconnect();
    }
}

function clearCanvas(canvasId) {
    const canvas = document.getElementById(canvasId);
    const ctx = canvas.getContext('2d');

    function drawFrame() {
        ctx.clearRect(0, 0, canvas.width, canvas.height);
        requestAnimationFrame(drawFrame);
    }
    drawFrame();
}