public static AudioFeature FromBytesXML(byte[] buf) { String xmlData = StringUtils.GetString(buf); XmlTextReader xmlTextReader = new XmlTextReader(new StringReader(xmlData)); MandelEllis mandelEllis = new MandelEllis(); mandelEllis.ReadXML(xmlTextReader); return(mandelEllis); }
/// <summary>Get Distance</summary> /// <seealso cref="">comirva.audio.feature.AudioFeature#GetDistance(comirva.audio.feature.AudioFeature)</seealso> public override double GetDistance(AudioFeature f) { if (!(f is MandelEllis)) { new Exception("Can only handle AudioFeatures of type Mandel Ellis, not of: " + f); return(-1); } MandelEllis other = (MandelEllis)f; return(KullbackLeibler(this.gmmMe, other.gmmMe) + KullbackLeibler(other.gmmMe, this.gmmMe)); }
public static AudioFeature FromBytesCompressed(byte[] byteArray) { using (Stream stream = new MemoryStream(byteArray)) { Matrix mean = Matrix.LoadBinary(stream); Matrix covarMatrix = Matrix.LoadBinary(stream); Matrix covarMatrixInv = Matrix.LoadBinary(stream); stream.Flush(); MandelEllis.GmmMe gmmme = new MandelEllis.GmmMe(mean, covarMatrix, covarMatrixInv); var mandelEllis = new MandelEllis(gmmme); return(mandelEllis); } }
public AudioFeature Calculate(double[] input) { //pack the mfccs into a pointlist double[][] mfccCoefficients = mfcc.Process(input); //check if element 0 exists if(mfccCoefficients.Length == 0) throw new ArgumentException("The input stream is to short to process;"); //create mfcc matrix Matrix mfccs = new Matrix(mfccCoefficients); #if DEBUG mfccs.WriteText("mfccdata-mandelellis.txt"); mfccs.DrawMatrixGraph("mfccdata-mandelellis.png"); #endif // compute mean //Matrix mean = mfccs.Mean(1).Transpose(); Matrix mean = mfccs.Mean(2); #if DEBUG mean.WriteText("mean-mandelellis.txt"); mean.DrawMatrixGraph("mean-mandelellis.png"); #endif // create covariance matrix Matrix covarMatrix = mfccs.Cov(); #if DEBUG covarMatrix.WriteText("covariance-mandelellis.txt"); covarMatrix.DrawMatrixGraph("covariance-mandelellis.png"); #endif // Inverse Covariance Matrix covarMatrixInv; try { //covarMatrixInv = covarMatrix.Inverse(); covarMatrixInv = covarMatrix.InverseGausJordan(); } catch (Exception) { Console.Error.WriteLine("Mandel Ellis Extraction Failed!"); return null; } #if DEBUG covarMatrixInv.WriteText("inverse_covariance-mandelellis.txt"); covarMatrixInv.DrawMatrixGraph("inverse_covariance-mandelellis.png"); #endif MandelEllis.GmmMe gmmMe = new MandelEllis.GmmMe(mean, covarMatrix, covarMatrixInv); MandelEllis mandelEllis = new MandelEllis(gmmMe); return mandelEllis; }
/// <summary>Get Distance</summary> /// <seealso cref="">comirva.audio.feature.AudioFeature#GetDistance(comirva.audio.feature.AudioFeature)</seealso> public override double GetDistance(AudioFeature f, AudioFeature.DistanceType t) { if (!(f is MandelEllis)) { new Exception("Can only handle AudioFeatures of type Mandel Ellis, not of: " + f); return(-1); } MandelEllis other = (MandelEllis)f; DistanceMeasure distanceMeasure = DistanceMeasure.Euclidean; switch (t) { case AudioFeature.DistanceType.Dtw_Euclidean: distanceMeasure = DistanceMeasure.Euclidean; break; case AudioFeature.DistanceType.Dtw_SquaredEuclidean: distanceMeasure = DistanceMeasure.SquaredEuclidean; break; case AudioFeature.DistanceType.Dtw_Manhattan: distanceMeasure = DistanceMeasure.Manhattan; break; case AudioFeature.DistanceType.Dtw_Maximum: distanceMeasure = DistanceMeasure.Maximum; break; case AudioFeature.DistanceType.KullbackLeiblerDivergence: default: return(KullbackLeibler(this.gmmMe, other.gmmMe) + KullbackLeibler(other.gmmMe, this.gmmMe)); } Dtw dtw = new Dtw(this.GetArray(), other.GetArray(), distanceMeasure, true, true, null, null, null); return(dtw.GetCost()); }
/// <summary> /// Find Similar Tracks to one or many audio files using their unique database id(s) /// </summary> /// <param name="id">an array of unique database ids for the audio files to search for similar matches</param> /// <param name="exclude">an array of unique database ids to ignore (normally the same as the id array)</param> /// <param name="db">database</param> /// <param name="analysisMethod">analysis method (SCMS or MandelEllis)</param> /// <param name="numToTake">max number of entries to return</param> /// <param name="percentage">percentage below and above the duration in ms when querying (used if between 0.1 - 0.9)</param> /// <param name="distanceType">distance method to use (KullbackLeiblerDivergence is default)</param> /// <returns>a list of query results</returns> public static List<FindSimilar.QueryResult> SimilarTracksList(int[] id, int[] exclude, Db db, Analyzer.AnalysisMethod analysisMethod, int numToTake=25, double percentage=0.2, AudioFeature.DistanceType distanceType = AudioFeature.DistanceType.KullbackLeiblerDivergence) { AudioFeature[] seedAudioFeatures = null; AudioFeature[] audioFeatures = null; switch (analysisMethod) { case Analyzer.AnalysisMethod.MandelEllis: seedAudioFeatures = new MandelEllis[id.Length]; audioFeatures = new MandelEllis[100]; break; case Analyzer.AnalysisMethod.SCMS: seedAudioFeatures = new Scms[id.Length]; audioFeatures = new Scms[100]; break; } for (int i = 0; i < seedAudioFeatures.Length; i++) { seedAudioFeatures[i] = db.GetTrack(id[i], analysisMethod); } // Get all tracks from the DB except the seedSongs IDataReader r = db.GetTracks(exclude, seedAudioFeatures[0].Duration, percentage); // store results in a query results list List<FindSimilar.QueryResult> queryResultList = new List<FindSimilar.QueryResult>(); int[] mapping = new int[100]; int read = 1; double d; double dcur; float count; while (read > 0) { read = db.GetNextTracks(ref r, ref audioFeatures, ref mapping, 100, analysisMethod); for (int i = 0; i < read; i++) { d = 0; count = 0; for (int j = 0; j < seedAudioFeatures.Length; j++) { dcur = seedAudioFeatures[j].GetDistance(audioFeatures[i], distanceType); // convert to positive values dcur = Math.Abs(dcur); d += dcur; count++; } if (d > 0) { QueryResult queryResult = new QueryResult(); queryResult.Id = mapping[i]; queryResult.Path = audioFeatures[i].Name; queryResult.Duration = audioFeatures[i].Duration; queryResult.Similarity = d/count; queryResultList.Add(queryResult); } } } var sortedList = (from row in queryResultList orderby row.Similarity ascending select new QueryResult { Id = row.Id, Path = row.Path, Duration = row.Duration, Similarity = row.Similarity }).Take(numToTake).ToList(); return sortedList; }
/// <summary> /// Find Similar Tracks to one or many audio files using their unique database id(s) /// </summary> /// <param name="id">an array of unique database ids for the audio files to search for similar matches</param> /// <param name="exclude">an array of unique database ids to ignore (normally the same as the id array)</param> /// <param name="db">database</param> /// <param name="analysisMethod">analysis method (SCMS or MandelEllis)</param> /// <param name="numToTake">max number of entries to return</param> /// <param name="percentage">percentage below and above the duration in ms when querying (used if between 0.1 - 0.9)</param> /// <param name="distanceType">distance method to use (KullbackLeiblerDivergence is default)</param> /// <returns>a dictinary list of key value pairs (filepath and distance)</returns> public static Dictionary<KeyValuePair<int, string>, double> SimilarTracks(int[] id, int[] exclude, Db db, Analyzer.AnalysisMethod analysisMethod, int numToTake=25, double percentage=0.2, AudioFeature.DistanceType distanceType = AudioFeature.DistanceType.KullbackLeiblerDivergence) { DbgTimer t = new DbgTimer(); t.Start(); AudioFeature[] seedAudioFeatures = null; AudioFeature[] audioFeatures = null; switch (analysisMethod) { case Analyzer.AnalysisMethod.MandelEllis: seedAudioFeatures = new MandelEllis[id.Length]; audioFeatures = new MandelEllis[100]; break; case Analyzer.AnalysisMethod.SCMS: seedAudioFeatures = new Scms[id.Length]; audioFeatures = new Scms[100]; break; } for (int i = 0; i < seedAudioFeatures.Length; i++) { seedAudioFeatures[i] = db.GetTrack(id[i], analysisMethod); } // Get all tracks from the DB except the seedSongs IDataReader r = db.GetTracks(exclude, seedAudioFeatures[0].Duration, percentage); // store results in a dictionary var NameDictionary = new Dictionary<KeyValuePair<int, string>, double>(); int[] mapping = new int[100]; int read = 1; double d; double dcur; float count; while (read > 0) { read = db.GetNextTracks(ref r, ref audioFeatures, ref mapping, 100, analysisMethod); for (int i = 0; i < read; i++) { d = 0; count = 0; for (int j = 0; j < seedAudioFeatures.Length; j++) { dcur = seedAudioFeatures[j].GetDistance(audioFeatures[i], distanceType); // convert to positive values dcur = Math.Abs(dcur); d += dcur; count++; } if (d > 0) { NameDictionary.Add(new KeyValuePair<int,string>(mapping[i], audioFeatures[i].Name), d/count); //NameDictionary.Add(new KeyValuePair<int,string>(mapping[i], String.Format("{0} ({1} ms)", audioFeatures[i].Name, audioFeatures[i].Duration)), d/count); } } } // sort by non unique values var sortedDict = (from entry in NameDictionary orderby entry.Value ascending select entry) .Take(numToTake) .ToDictionary(pair => pair.Key, pair => pair.Value); Console.Out.WriteLine(String.Format("Found Similar to ({0}) in {1} ms", String.Join(",", seedAudioFeatures.Select(p=>p.Name)), t.Stop().TotalMilliseconds)); return sortedDict; }
/// <summary> /// Find Similar Tracks to an audio file using its file path /// </summary> /// <param name="searchForPath">audio file path</param> /// <param name="db">database</param> /// <param name="analysisMethod">analysis method (SCMS or MandelEllis)</param> /// <param name="numToTake">max number of entries to return</param> /// <param name="percentage">percentage below and above the duration in ms when querying (used if between 0.1 - 0.9)</param> /// <param name="distanceType">distance method to use (KullbackLeiblerDivergence is default)</param> /// <returns>a list of query results</returns> public static List<FindSimilar.QueryResult> SimilarTracksList(string searchForPath, Db db, Analyzer.AnalysisMethod analysisMethod, int numToTake=25, double percentage=0.2, AudioFeature.DistanceType distanceType = AudioFeature.DistanceType.KullbackLeiblerDivergence) { FileInfo fi = new FileInfo(searchForPath); AudioFeature seedAudioFeature = null; AudioFeature[] audioFeatures = null; switch (analysisMethod) { case Analyzer.AnalysisMethod.MandelEllis: seedAudioFeature = Analyzer.AnalyzeMandelEllis(fi); audioFeatures = new MandelEllis[100]; break; case Analyzer.AnalysisMethod.SCMS: seedAudioFeature = Analyzer.AnalyzeScms(fi); audioFeatures = new Scms[100]; break; } // Get all tracks from the DB except the seedSongs IDataReader r = db.GetTracks(null, seedAudioFeature.Duration, percentage); // store results in a query results list List<FindSimilar.QueryResult> queryResultList = new List<FindSimilar.QueryResult>(); int[] mapping = new int[100]; int read = 1; double dcur; while (read > 0) { read = db.GetNextTracks(ref r, ref audioFeatures, ref mapping, 100, analysisMethod); for (int i = 0; i < read; i++) { dcur = seedAudioFeature.GetDistance(audioFeatures[i], distanceType); // convert to positive values dcur = Math.Abs(dcur); QueryResult queryResult = new QueryResult(); queryResult.Id = mapping[i]; queryResult.Path = audioFeatures[i].Name; queryResult.Duration = audioFeatures[i].Duration; queryResult.Similarity = dcur; queryResultList.Add(queryResult); } } var sortedList = (from row in queryResultList orderby row.Similarity ascending select new QueryResult { Id = row.Id, Path = row.Path, Duration = row.Duration, Similarity = row.Similarity }).Take(numToTake).ToList(); return sortedList; }
/// <summary> /// Find Similar Tracks to an audio file using its file path /// </summary> /// <param name="searchForPath">audio file path</param> /// <param name="db">database</param> /// <param name="analysisMethod">analysis method (SCMS or MandelEllis)</param> /// <param name="numToTake">max number of entries to return</param> /// <param name="percentage">percentage below and above the duration in ms when querying (used if between 0.1 - 0.9)</param> /// <param name="distanceType">distance method to use (KullbackLeiblerDivergence is default)</param> /// <returns>a dictinary list of key value pairs (filepath and distance)</returns> public static Dictionary<KeyValuePair<int, string>, double> SimilarTracks(string searchForPath, Db db, Analyzer.AnalysisMethod analysisMethod, int numToTake=25, double percentage=0.2, AudioFeature.DistanceType distanceType = AudioFeature.DistanceType.KullbackLeiblerDivergence) { DbgTimer t = new DbgTimer(); t.Start(); FileInfo fi = new FileInfo(searchForPath); AudioFeature seedAudioFeature = null; AudioFeature[] audioFeatures = null; switch (analysisMethod) { case Analyzer.AnalysisMethod.MandelEllis: seedAudioFeature = Analyzer.AnalyzeMandelEllis(fi); audioFeatures = new MandelEllis[100]; break; case Analyzer.AnalysisMethod.SCMS: seedAudioFeature = Analyzer.AnalyzeScms(fi); audioFeatures = new Scms[100]; break; } // Get all tracks from the DB except the seedSongs IDataReader r = db.GetTracks(null, seedAudioFeature.Duration, percentage); // store results in a dictionary var NameDictionary = new Dictionary<KeyValuePair<int, string>, double>(); int[] mapping = new int[100]; int read = 1; double dcur; while (read > 0) { read = db.GetNextTracks(ref r, ref audioFeatures, ref mapping, 100, analysisMethod); for (int i = 0; i < read; i++) { dcur = seedAudioFeature.GetDistance(audioFeatures[i], distanceType); // convert to positive values dcur = Math.Abs(dcur); NameDictionary.Add(new KeyValuePair<int,string>(mapping[i], audioFeatures[i].Name), dcur); } } // sort by non unique values var sortedDict = (from entry in NameDictionary orderby entry.Value ascending select entry) .Take(numToTake) .ToDictionary(pair => pair.Key, pair => pair.Value); Console.Out.WriteLine(String.Format("Found Similar to ({0}) in {1} ms", seedAudioFeature.Name, t.Stop().TotalMilliseconds)); return sortedDict; }
public static AudioFeature FromBytesXML(byte[] buf) { String xmlData = StringUtils.GetString(buf); XmlTextReader xmlTextReader = new XmlTextReader(new StringReader(xmlData)); MandelEllis mandelEllis = new MandelEllis(); mandelEllis.ReadXML(xmlTextReader); return mandelEllis; }
public static AudioFeature FromBytesCompressed(byte[] byteArray) { using (Stream stream = new MemoryStream(byteArray)) { Matrix mean = Matrix.LoadBinary(stream); Matrix covarMatrix = Matrix.LoadBinary(stream); Matrix covarMatrixInv = Matrix.LoadBinary(stream); stream.Flush(); MandelEllis.GmmMe gmmme = new MandelEllis.GmmMe(mean, covarMatrix, covarMatrixInv); var mandelEllis = new MandelEllis(gmmme); return mandelEllis; } }