how to make a dictionary that can hold more than 1 data?

Question

i've been trying to modify the program so that it could accept more than one data for a single alphabet character for example letter "A". there were some sort of ContainsKey function that allow only one key from keyboard to hold only one data. how to make it possible to hold more than one data?

I'm gonna make it very clear, this is an online OCR program using unsupervised neural network. when a user draw a character in the drawing space, they will have the option to add the character into the learning data to be train later. when they add a character, they have to define what character they just entered using the key on the keyboard. for example, they draw letter 'A' and a popup window will show up asking the user to enter the key from the keyboard for that letter.

the problem here, when there is already a letter 'A' in the learning data, i cannot add another letter 'A' bcause the key A is already hold the previous 'A'. i wanted to make the key A is able to hold more than one letter 'A'.

im gonna post the whole code for the program here and i hope u guys bear with me. this isnt my program, it is from Heaton Research and i just intend to modify it. thank in advance.

  public partial class Form1 : Form
  {
  /**
  * The downsample width for the application.
  */
    const int DOWNSAMPLE_WIDTH = 10;

    /**
     * The down sample height for the application.
     */
    const int DOWNSAMPLE_HEIGHT = 12;

    private Bitmap entryImage;
    private Graphics entryGraphics;
    private int entryLastX;
    private int entryLastY;
    private Pen blackPen;
    private bool[] downsampled;
    private Dictionary<char, List<bool[]>> letterData = new Dictionary<Char, List<bool[]>>();
    private double[][] trainingSet;
    private SelfOrganizingMap network;

    public Form1()
    {
        InitializeComponent();
        blackPen = new Pen(Color.Black);
        entryImage = new Bitmap(entry.Width, entry.Height);
        entryGraphics = Graphics.FromImage(entryImage);
        downsampled = new bool[Form1.DOWNSAMPLE_HEIGHT * Form1.DOWNSAMPLE_WIDTH];
        ClearEntry();
    }

    private void entry_Paint(object sender, PaintEventArgs e)
    {
        Graphics g = e.Graphics;
        g.DrawImage(entryImage, 0, 0);
        Pen blackPen = new Pen(Color.Black);
        g.DrawRectangle(blackPen, 0, 0, entry.Width - 1, entry.Height - 1);

    }

    private void btnDelete_Click(object sender, EventArgs e)
    {
        string str = (string)this.letters.Items[this.letters.SelectedIndex]; 
        char ch = str[0];
        this.letterData.Remove(ch);
        this.letters.Items.Remove(str);
        ClearEntry();
    }

    private void btnLoad_Click(object sender, EventArgs e)
    {
        try
        {

            OpenFileDialog openFileDialog1 = new OpenFileDialog();
            openFileDialog1.Filter = "Data File (*.dat)|*.dat";
            if (openFileDialog1.ShowDialog() == DialogResult.OK)
            {

                TextReader f = new StreamReader(openFileDialog1.FileName);

                String line;

                this.letterData.Clear();
                this.letters.Items.Clear();

                while ((line = f.ReadLine()) != null)
                {
                    int sampleSize = Form1.DOWNSAMPLE_HEIGHT * Form1.DOWNSAMPLE_WIDTH;
                    char ch = char.ToUpper(line[0]);
                    bool[] sample = new bool[sampleSize];

                    int idx = 2;
                    for (int i = 0; i < sampleSize; i++)
                    {
                        if (line[idx++] == '1')
                            sample[i] = true;
                        else
                            sample[i] = false;
                    }

                    this.letterData.Add(ch, sample);
                    this.letters.Items.Add("" + ch);
                }

                f.Close();
            }
            MessageBox.Show(this, "File Loaded");

        }
        catch (Exception ex)
        {
            MessageBox.Show("Error: " + ex.Message);
        }
    }

    private void btnSave_Click(object sender, EventArgs e)
    {
        try
        {
             SaveFileDialog saveFileDialog1 = new SaveFileDialog();
            saveFileDialog1.Filter = "Data File (*.dat)|*.dat";
             if (saveFileDialog1.ShowDialog() == DialogResult.OK)
             {
                 TextWriter f = new StreamWriter(saveFileDialog1.FileName);
                 int size = Form1.DOWNSAMPLE_HEIGHT * Form1.DOWNSAMPLE_WIDTH;

                 for (int i = 0; i < this.letters.Items.Count; i++)
                 {
                     char ch = ((string)this.letters.Items[i])[0];
                     bool[] data = this.letterData[ch];

                     f.Write(ch + ":");
                     for (int j = 0; j < size; j++)
                     {
                         f.Write(data[j] ? "1" : "0");

                     }
                     f.WriteLine("");


                 }
                 f.Close();

                 MessageBox.Show("File Saved");

             }
        }
        catch (Exception e2)
        {
            MessageBox.Show("Error: " + e2.Message, "Training");
        }
    }

    private void btnBeginTraining_Click(object sender, EventArgs e)
    {
        int inputCount = Form1.DOWNSAMPLE_HEIGHT * Form1.DOWNSAMPLE_WIDTH;
        int letterCount = this.letters.Items.Count;
        this.trainingSet = new double[letterCount][];
        int index = 0;
        foreach (char ch in this.letterData.Keys)
        {
            this.trainingSet[index] = new double[inputCount];
            bool[] data = this.letterData[ch];
            for (int i = 0; i < inputCount; i++)
            {
                this.trainingSet[index][i] = data[i] ? 0.5 : -0.5;
            }
            index++;
        }

        network = new SelfOrganizingMap(inputCount, letterCount, NormalizationType.Z_AXIS);

        this.ThreadProc();

    }

    private void btnAdd_Click(object sender, EventArgs e)
    {
        DownSample ds = new DownSample(this.entryImage);
        this.downsampled = ds.downSample(Form1.DOWNSAMPLE_WIDTH, Form1.DOWNSAMPLE_HEIGHT);
        this.sample.Invalidate();
        String Prompt = "Enter the letter you just draw (from the keyboard)";
        String Title = "Letter definition Required";
        String Default = " ";
        Int32 XPos = ((SystemInformation.WorkingArea.Width / 2) - 200);
        Int32 YPos = ((SystemInformation.WorkingArea.Height / 2) - 100);

        bool valid = false;
        for (int i = 0; i < this.downsampled.Length; i++)
        {
            if (this.downsampled[i])
            {
                valid = true;
            }
         }


        if (!valid)
        {
            MessageBox.Show("Please draw a letter before adding it.");
            return;
        }



       String Result = Microsoft.VisualBasic.Interaction.InputBox(Prompt, Title, Default, XPos, YPos);
       if (Result != null)
       {
           Result = Result.ToUpper();
           if (Result.Length == 0)
           {
               MessageBox.Show("Please enter a character.");
           }
           else if (Result.Length < 1)
           {
               MessageBox.Show("Please enter only a single character.");
           }
           //else if (this.letterData.ContainsKey(Result[0]))
           //{
           //    MessageBox.Show("That letter is already defined, please delete first.");
           //}
           else
           {
               if (this.letterData.ContainsKey(Result[0]))
               {
                   this.letterData[Result[0]].Add(this.downsampled);
               }
               else
               {
                   this.letterData.Add(Result[0], new List<bool[]>() {this.downsampled});
               }

               this.letters.Items.Add(Result);
               //this.letterData.Add(Result[0], this.downsampled);
               this.ClearEntry();
           }
       }


    }

    private void btnRecognize_Click(object sender, EventArgs e)
    {
        DownSample ds = new DownSample(this.entryImage);
        this.downsampled = ds.downSample(Form1.DOWNSAMPLE_WIDTH, Form1.DOWNSAMPLE_HEIGHT);
        this.sample.Invalidate();

        if (this.network == null)
        {
            MessageBox.Show("The program needs to be trained first");
            return;
        }

        int sampleSize = Form1.DOWNSAMPLE_HEIGHT * Form1.DOWNSAMPLE_WIDTH;
        double[] input = new double[sampleSize];

        for (int i = 0; i < sampleSize; i++)
        {
            input[i] = this.downsampled[i] ? 0.5 : -0.5;
        }

        int best = this.network.Winner(input);
        char[] map = mapNeurons();
        this.result.Text = "  " + map[best];
        MessageBox.Show("  " + map[best] + "   (Neuron #"
                        + best + " fired)", "That Letter You Enter Is");
        //ClearEntry();
    }

    private void btnClear_Click(object sender, EventArgs e)
    {
        ClearEntry();
    }

    private void btnSample_Click(object sender, EventArgs e)
    {
        DownSample ds = new DownSample(this.entryImage);
        this.downsampled = ds.downSample(Form1.DOWNSAMPLE_WIDTH, Form1.DOWNSAMPLE_HEIGHT);
        this.sample.Invalidate();
    }
    public void ClearEntry()
    {
        Brush whiteBrush = new SolidBrush(Color.White);
        entryGraphics.FillRectangle(whiteBrush, 0, 0, entry.Width, entry.Height);
        entry.Invalidate();
        DownSample ds = new DownSample(this.entryImage);
        this.downsampled = ds.downSample(Form1.DOWNSAMPLE_WIDTH, Form1.DOWNSAMPLE_HEIGHT);
        this.sample.Invalidate();
    }

    private void entry_MouseDown(object sender, MouseEventArgs e)
    {
        entry.Capture = true;
        entryLastX = e.X;
        entryLastY = e.Y;
    }

    private void entry_MouseUp(object sender, MouseEventArgs e)
    {
        entryGraphics.DrawLine(blackPen, entryLastX, entryLastY, e.X, e.Y);
        entry.Invalidate();
        entry.Capture = false;
    }

    private void entry_MouseMove(object sender, MouseEventArgs e)
    {
        if (entry.Capture == true)
        {
            entryGraphics.DrawLine(blackPen, entryLastX, entryLastY, e.X, e.Y);
            entry.Invalidate();
            entryLastX = e.X;
            entryLastY = e.Y;
        }
    }

    private void sample_Paint(object sender, PaintEventArgs e)
    {
        Graphics g = e.Graphics;

        int x, y;
        int vcell = sample.Height / Form1.DOWNSAMPLE_HEIGHT;
        int hcell = sample.Width / Form1.DOWNSAMPLE_WIDTH;
        Brush whiteBrush = new SolidBrush(Color.White);
        Brush blackBrush = new SolidBrush(Color.Black);
        Pen blackPen = new Pen(Color.Black);

        g.FillRectangle(whiteBrush, 0, 0, sample.Width, sample.Height);



        for (y = 0; y < Form1.DOWNSAMPLE_HEIGHT; y++)
        {
            g.DrawLine(blackPen, 0, y * vcell, sample.Width, y * vcell);
        }
        for (x = 0; x < Form1.DOWNSAMPLE_WIDTH; x++)
        {
            g.DrawLine(blackPen, x * hcell, 0, x * hcell, sample.Height);
        }

        int index = 0;
        for (y = 0; y < Form1.DOWNSAMPLE_HEIGHT; y++)
        {
            for (x = 0; x < Form1.DOWNSAMPLE_WIDTH; x++)
            {
                if (this.downsampled[index++])
                {
                    g.FillRectangle(blackBrush, x * hcell, y * vcell, hcell, vcell);
                }
            }
        }

        g.DrawRectangle(blackPen, 0, 0, sample.Width - 1, sample.Height - 1);
    }

    private void letters_SelectedIndexChanged(object sender, EventArgs e)
    {
        if (this.letters.SelectedIndex >= 0)
        {
            string str = (string)this.letters.Items[this.letters.SelectedIndex];
            char ch = str[0];
            this.downsampled = this.letterData[ch];
            this.sample.Invalidate();
        }
    }

    public void ThreadProc()
    {
        TrainSelfOrganizingMap train = new TrainSelfOrganizingMap(
            this.network, this.trainingSet, TrainSelfOrganizingMap.LearningMethod.SUBTRACTIVE, 0.5);

        int tries = 1;

        do
        {
            train.Iteration();
            this.txtTries.Text = "" + tries;
            this.txtBestError.Text = "" + train.BestError;
            this.txtLastError.Text = "" + train.TotalError;
            tries++;
            Application.DoEvents();
        } while (train.TotalError > 0.01 && (tries <= 100));
        MessageBox.Show("Training complete.");
    }

    /**
     * Used to map neurons to actual letters.
     * 
     * @return The current mapping between neurons and letters as an array.
     */
    public char[] mapNeurons()
    {
        char[] map = new char[this.letters.Items.Count];

        for (int i = 0; i < map.Length; i++)
        {
            map[i] = '?';
        }
        for (int i = 0; i < this.letters.Items.Count; i++)
        {
            double[] input = new double[Form1.DOWNSAMPLE_HEIGHT * Form1.DOWNSAMPLE_WIDTH];
            char ch = ((string)(this.letters.Items[i]))[0];
            bool[] data = this.letterData[ch];
            for (int j = 0; j < input.Length; j++)
            {
                input[j] = data[j] ? 0.5 : -0.5;
            }

            int best = this.network.Winner(input);
            map[best] = ch;
        }
        return map;
    }

}