diff --git a/.gitattributes b/.gitattributes
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+storage/** filter=lfs diff=lfs merge=lfs -text
diff --git a/server/api/atc/audio/[...path].get.ts b/server/api/atc/audio/[...path].get.ts
new file mode 100644
index 0000000..e69de29
diff --git a/server/api/atc/ptt.post.ts b/server/api/atc/ptt.post.ts
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+// server/api/atc/ptt.post.ts
+import { createError, readBody } from "h3";
+import { writeFile, readFile, mkdir, rm } from "node:fs/promises";
+import { existsSync } from "node:fs";
+import { join } from "node:path";
+import { tmpdir } from "node:os";
+import { randomUUID } from "node:crypto";
+import { execFile } from "node:child_process";
+import { openai, LLM_MODEL, normalizeATC } from "../../utils/openai";
+
+interface PTTRequest {
+    audio: string; // Base64 encoded audio
+    expectedText: string; // Was der Nutzer wiederholen sollte
+    moduleId: string;
+    lessonId: string;
+    format?: 'wav' | 'mp3' | 'ogg' | 'webm'; // Audio format
+}
+
+interface PTTResponse {
+    success: boolean;
+    transcription: string;
+    normalized: string;
+    expectedNormalized: string;
+    evaluation: {
+        score: number; // 0-100
+        accuracy: number; // Text similarity
+        keywordMatch: number; // Keyword matching
+        recommendation: 'excellent' | 'good' | 'retry' | 'listen_again';
+        feedback: string;
+        mistakes?: string[];
+    };
+    playAgain: boolean; // Ob der ursprüngliche Funkspruch nochmal abgespielt werden soll
+}
+
+async function sh(cmd: string, args: string[]) {
+    return new Promise<{ stdout: string; stderr: string }>((res, rej) =>
+        execFile(cmd, args, { encoding: 'utf8' }, (err, stdout, stderr) =>
+            err ? rej(new Error(stderr || String(err))) : res({ stdout, stderr })
+        )
+    );
+}
+
+// Audio zu WAV konvertieren für bessere Whisper-Kompatibilität
+async function convertToWav(inputPath: string, outputPath: string) {
+    await sh("ffmpeg", [
+        "-y", "-i", inputPath,
+        "-ar", "16000",  // 16kHz für Whisper
+        "-ac", "1",      // Mono
+        "-f", "wav",
+        outputPath
+    ]);
+}
+
+// Levenshtein Distance für Text-Ähnlichkeit
+function levenshteinDistance(str1: string, str2: string): number {
+    const matrix = Array(str2.length + 1).fill(null).map(() => Array(str1.length + 1).fill(null));
+
+    for (let i = 0; i <= str1.length; i++) matrix[0][i] = i;
+    for (let j = 0; j <= str2.length; j++) matrix[j][0] = j;
+
+    for (let j = 1; j <= str2.length; j++) {
+        for (let i = 1; i <= str1.length; i++) {
+            const indicator = str1[i - 1] === str2[j - 1] ? 0 : 1;
+            matrix[j][i] = Math.min(
+                matrix[j][i - 1] + 1,     // deletion
+                matrix[j - 1][i] + 1,     // insertion
+                matrix[j - 1][i - 1] + indicator // substitution
+            );
+        }
+    }
+
+    return matrix[str2.length][str1.length];
+}
+
+function calculateSimilarity(str1: string, str2: string): number {
+    const distance = levenshteinDistance(str1.toLowerCase(), str2.toLowerCase());
+    const maxLength = Math.max(str1.length, str2.length);
+    return maxLength === 0 ? 1 : (maxLength - distance) / maxLength;
+}
+
+// Extrahiere Keywords für ATC-spezifische Bewertung
+function extractATCKeywords(text: string): string[] {
+    const atcKeywords = [
+        // Callsigns
+        'lufthansa', 'speedbird', 'air france', 'klm', 'american', 'united', 'delta', 'ryanair', 'easy',
+        // Numbers/Letters
+        'alpha', 'bravo', 'charlie', 'delta', 'echo', 'foxtrot', 'golf', 'hotel', 'india', 'juliett',
+        'kilo', 'lima', 'mike', 'november', 'oscar', 'papa', 'quebec', 'romeo', 'sierra', 'tango',
+        'uniform', 'victor', 'whiskey', 'x-ray', 'yankee', 'zulu',
+        'zero', 'wun', 'too', 'tree', 'fower', 'fife', 'six', 'seven', 'eight', 'niner',
+        // ATC Phraseology
+        'runway', 'taxi', 'contact', 'ground', 'tower', 'approach', 'departure',
+        'cleared', 'hold short', 'line up', 'wait', 'takeoff', 'landing', 'vacate',
+        'via', 'squawk', 'heading', 'altitude', 'flight level', 'decimal',
+        'roger', 'affirm', 'negative', 'unable', 'standby', 'say again'
+    ];
+
+    const normalized = text.toLowerCase().replace(/[^\w\s]/g, ' ').replace(/\s+/g, ' ').trim();
+    return atcKeywords.filter(keyword => normalized.includes(keyword));
+}
+
+async function evaluateReadback(transcription: string, expected: string, moduleId: string, lessonId: string) {
+    const normalizedTranscription = normalizeATC(transcription);
+    const normalizedExpected = normalizeATC(expected);
+
+    // Text-Ähnlichkeit
+    const accuracy = calculateSimilarity(normalizedTranscription, normalizedExpected);
+
+    // Keyword-Matching für ATC-spezifische Begriffe
+    const expectedKeywords = extractATCKeywords(normalizedExpected);
+    const transcribedKeywords = extractATCKeywords(normalizedTranscription);
+    const keywordMatch = expectedKeywords.length > 0
+        ? transcribedKeywords.filter(k => expectedKeywords.includes(k)).length / expectedKeywords.length
+        : 1;
+
+    // Gewichtete Gesamtbewertung
+    const score = Math.round((accuracy * 0.6 + keywordMatch * 0.4) * 100);
+
+    // LLM für detailliertes Feedback
+    const prompt = `You are an ATC instructor evaluating a pilot's readback.
+
+Expected: "${expected}"
+Pilot said: "${transcription}"
+
+Module: ${moduleId}, Lesson: ${lessonId}
+
+Evaluate the readback and provide:
+1. Brief feedback (max 2 sentences)
+2. Specific mistakes if any
+3. Overall assessment
+
+Be constructive and educational. Focus on aviation safety and standard phraseology.
+
+Response format:
+FEEDBACK: [your feedback]
+MISTAKES: [list mistakes or "None"]
+ASSESSMENT: [excellent/good/needs_improvement/unacceptable]`;
+
+    try {
+        const completion = await openai.chat.completions.create({
+            model: LLM_MODEL,
+            messages: [{ role: "user", content: prompt }],
+            max_tokens: 300,
+            temperature: 0.3
+        });
+
+        const response = completion.choices[0]?.message?.content || "";
+        const feedback = response.match(/FEEDBACK: (.+?)(?=MISTAKES:|$)/)?.[1]?.trim() || "Good attempt.";
+        const mistakes = response.match(/MISTAKES: (.+?)(?=ASSESSMENT:|$)/)?.[1]?.trim();
+        const assessment = response.match(/ASSESSMENT: (.+)/)?.[1]?.trim() || "good";
+
+        let recommendation: PTTResponse['evaluation']['recommendation'] = 'good';
+        let playAgain = false;
+
+        if (score >= 90) {
+            recommendation = 'excellent';
+        } else if (score >= 75) {
+            recommendation = 'good';
+        } else if (score >= 50) {
+            recommendation = 'retry';
+            playAgain = true;
+        } else {
+            recommendation = 'listen_again';
+            playAgain = true;
+        }
+
+        return {
+            score,
+            accuracy,
+            keywordMatch,
+            recommendation,
+            feedback,
+            mistakes: mistakes && mistakes !== "None" ? [mistakes] : undefined,
+            playAgain
+        };
+
+    } catch (error) {
+        console.error("LLM evaluation failed:", error);
+
+        // Fallback ohne LLM
+        let recommendation: PTTResponse['evaluation']['recommendation'] = 'good';
+        let playAgain = false;
+
+        if (score >= 90) {
+            recommendation = 'excellent';
+        } else if (score >= 75) {
+            recommendation = 'good';
+        } else if (score >= 50) {
+            recommendation = 'retry';
+            playAgain = true;
+        } else {
+            recommendation = 'listen_again';
+            playAgain = true;
+        }
+
+        return {
+            score,
+            accuracy,
+            keywordMatch,
+            recommendation,
+            feedback: score >= 75 ? "Good readback!" : "Try to match the phraseology more closely.",
+            playAgain
+        };
+    }
+}
+
+export default defineEventHandler(async (event) => {
+    const body = await readBody<PTTRequest>(event);
+
+    if (!body.audio || !body.expectedText || !body.moduleId || !body.lessonId) {
+        throw createError({
+            statusCode: 400,
+            statusMessage: "audio, expectedText, moduleId, and lessonId are required"
+        });
+    }
+
+    const id = randomUUID();
+    const tmpAudioInput = join(tmpdir(), `ptt-input-${id}.${body.format || 'wav'}`);
+    const tmpAudioWav = join(tmpdir(), `ptt-wav-${id}.wav`);
+
+    try {
+        // 1. Audio aus Base64 dekodieren und speichern
+        const audioBuffer = Buffer.from(body.audio, 'base64');
+        await writeFile(tmpAudioInput, audioBuffer);
+
+        // 2. Zu WAV konvertieren falls nötig
+        if (body.format !== 'wav') {
+            await convertToWav(tmpAudioInput, tmpAudioWav);
+        }
+
+        const audioFileForWhisper = body.format === 'wav' ? tmpAudioInput : tmpAudioWav;
+
+        // 3. OpenAI Whisper für Transkription
+        const transcription = await openai.audio.transcriptions.create({
+            file: await readFile(audioFileForWhisper),
+            model: "whisper-1",
+            language: "en", // ATC ist standardmäßig auf Englisch
+            prompt: "This is ATC radio communication with aviation phraseology including callsigns, runway numbers, and standard procedures.",
+        });
+
+        const transcribedText = transcription.text.trim();
+
+        if (!transcribedText) {
+            throw createError({
+                statusCode: 400,
+                statusMessage: "No speech detected in audio"
+            });
+        }
+
+        // 4. Evaluation der Readback
+        const evaluation = await evaluateReadback(
+            transcribedText,
+            body.expectedText,
+            body.moduleId,
+            body.lessonId
+        );
+
+        // 5. Cleanup
+        await rm(tmpAudioInput).catch(() => {});
+        if (body.format !== 'wav') {
+            await rm(tmpAudioWav).catch(() => {});
+        }
+
+        return {
+            success: true,
+            transcription: transcribedText,
+            normalized: normalizeATC(transcribedText),
+            expectedNormalized: normalizeATC(body.expectedText),
+            evaluation,
+            playAgain: evaluation.playAgain
+        } as PTTResponse;
+
+    } catch (error) {
+        // Cleanup bei Fehler
+        await rm(tmpAudioInput).catch(() => {});
+        await rm(tmpAudioWav).catch(() => {});
+
+        if (error.statusCode) {
+            throw error;
+        }
+
+        throw createError({
+            statusCode: 500,
+            statusMessage: `PTT processing failed: ${error}`
+        });
+    }
+});
diff --git a/server/utils/atcPhrases.ts b/server/utils/atcPhrases.ts
new file mode 100644
index 0000000..e69de29